Prep for 2.6.1v2.6.1

7 files changed, 18 insertions, 18 deletions

diff --git a/Include/patchlevel.h b/Include/patchlevel.h
index 8a13a7c..55fe65e 100644
--- a/Include/patchlevel.h
+++ b/Include/patchlevel.h
@@ -22,12 +22,12 @@
 /*--start constants--*/
 #define PY_MAJOR_VERSION	2
 #define PY_MINOR_VERSION	6
-#define PY_MICRO_VERSION	0
+#define PY_MICRO_VERSION	1
 #define PY_RELEASE_LEVEL	PY_RELEASE_LEVEL_FINAL
 #define PY_RELEASE_SERIAL	0
 
 /* Version as a string */
-#define PY_VERSION      	"2.6+"
+#define PY_VERSION      	"2.6.1"
 /*--end constants--*/
 
 /* Subversion Revision number of this file (not of the repository) */
diff --git a/Lib/distutils/__init__.py b/Lib/distutils/__init__.py
index 7315a37..8f7eb84 100644
--- a/Lib/distutils/__init__.py
+++ b/Lib/distutils/__init__.py
@@ -22,5 +22,5 @@ __revision__ = "$Id$"
 #
 
 #--start constants--
-__version__ = "2.6"
+__version__ = "2.6.1"
 #--end constants--
diff --git a/Lib/idlelib/idlever.py b/Lib/idlelib/idlever.py
index 1071ada..2035267 100644
--- a/Lib/idlelib/idlever.py
+++ b/Lib/idlelib/idlever.py
@@ -1 +1 @@
-IDLE_VERSION = "2.6"
+IDLE_VERSION = "2.6.1"
diff --git a/Lib/pydoc_topics.py b/Lib/pydoc_topics.py
index c7d2674..247d4f6 100644
--- a/Lib/pydoc_topics.py
+++ b/Lib/pydoc_topics.py
@@ -1,9 +1,9 @@
-# Autogenerated by Sphinx on Thu Oct  2 17:24:06 2008
+# Autogenerated by Sphinx on Wed Dec  3 21:11:28 2008
 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 a sequence 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 a sequence 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* 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(In the current implementation, the syntax for targets is taken to be\nthe same as for expressions, and invalid syntax is rejected during the\ncode generation phase, causing less 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 ::= target augop (expression_list | yield_expression)\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 initial value is\nretrieved with a ``getattr()`` and the result is assigned with a\n``setattr()``.  Notice that the two methods do not necessarily refer\nto the same variable.  When ``getattr()`` refers to a class variable,\n``setattr()`` still writes to an instance variable. For example:\n\n   class A:\n       x = 3    # class variable\n   a = A()\n   a.x += 1     # writes a.x as 4 leaving A.x as 3\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',
  'atom-literals': u"\nLiterals\n********\n\nPython supports string literals and various numeric literals:\n\n   literal ::= stringliteral | integer | longinteger\n               | floatnumber | imagnumber\n\nEvaluation of a literal yields an object of the given type (string,\ninteger, long integer, floating point number, complex number) with the\ngiven value.  The value may be approximated in the case of floating\npoint and imaginary (complex) literals.  See section *Literals* for\ndetails.\n\nAll literals correspond to immutable data types, and hence the\nobject's identity is less important than its value.  Multiple\nevaluations of literals with the same value (either the same\noccurrence in the program text or a different occurrence) may obtain\nthe same object or a different object with the same value.\n",
- 'attribute-access': u'\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\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     builtin 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.  Normally, data\ndescriptors define both ``__get__()`` and ``__set__()``, while non-\ndata descriptors have just the ``__get__()`` method.  Data descriptors\nalways override a redefinition in an instance dictionary.  In\ncontrast, non-data descriptors can be overridden by instances. [2]\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* 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* 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__*.\n\n* *__slots__* do not work for classes derived from "variable-length"\n  built-in types such as ``long``, ``str`` and ``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',
+ 'attribute-access': u'\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\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     builtin 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.  Normally, data\ndescriptors define both ``__get__()`` and ``__set__()``, while non-\ndata descriptors have just the ``__get__()`` method.  Data descriptors\nalways override a redefinition in an instance dictionary.  In\ncontrast, non-data descriptors can be overridden by instances. [2]\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* 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* 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__*.\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',
  'attribute-references': u'\nAttribute references\n********************\n\nAn attribute reference is a primary followed by a period and a name:\n\n   attributeref ::= primary "." identifier\n\nThe primary must evaluate to an object of a type that supports\nattribute references, e.g., a module, list, or an instance.  This\nobject is then asked to produce the attribute whose name is the\nidentifier.  If this attribute is not available, the exception\n``AttributeError`` is raised. Otherwise, the type and value of the\nobject produced is determined by the object.  Multiple evaluations of\nthe same attribute reference may yield different objects.\n',
  'augassign': u'\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 ::= target augop (expression_list | yield_expression)\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 initial value is\nretrieved with a ``getattr()`` and the result is assigned with a\n``setattr()``.  Notice that the two methods do not necessarily refer\nto the same variable.  When ``getattr()`` refers to a class variable,\n``setattr()`` still writes to an instance variable. For example:\n\n   class A:\n       x = 3    # class variable\n   a = A()\n   a.x += 1     # writes a.x as 4 leaving A.x as 3\n',
  'binary': u'\nBinary arithmetic operations\n****************************\n\nThe binary arithmetic operations have the conventional priority\nlevels.  Note that some of these operations also apply to certain non-\nnumeric types.  Apart from the power operator, there are only two\nlevels, one for multiplicative operators and one for additive\noperators:\n\n   m_expr ::= u_expr | m_expr "*" u_expr | m_expr "//" u_expr | m_expr "/" u_expr\n              | m_expr "%" u_expr\n   a_expr ::= m_expr | a_expr "+" m_expr | a_expr "-" m_expr\n\nThe ``*`` (multiplication) operator yields the product of its\narguments.  The arguments must either both be numbers, or one argument\nmust be an integer (plain or long) and the other must be a sequence.\nIn the former case, the numbers are converted to a common type and\nthen multiplied together.  In the latter case, sequence repetition is\nperformed; a negative repetition factor yields an empty sequence.\n\nThe ``/`` (division) and ``//`` (floor division) operators yield the\nquotient of their arguments.  The numeric arguments are first\nconverted to a common type. Plain or long integer division yields an\ninteger of the same type; the result is that of mathematical division\nwith the \'floor\' function applied to the result. Division by zero\nraises the ``ZeroDivisionError`` exception.\n\nThe ``%`` (modulo) operator yields the remainder from the division of\nthe first argument by the second.  The numeric arguments are first\nconverted to a common type.  A zero right argument raises the\n``ZeroDivisionError`` exception.  The arguments may be floating point\nnumbers, e.g., ``3.14%0.7`` equals ``0.34`` (since ``3.14`` equals\n``4*0.7 + 0.34``.)  The modulo operator always yields a result with\nthe same sign as its second operand (or zero); the absolute value of\nthe result is strictly smaller than the absolute value of the second\noperand [2].\n\nThe integer division and modulo operators are connected by the\nfollowing identity: ``x == (x/y)*y + (x%y)``.  Integer division and\nmodulo are also connected with the built-in function ``divmod()``:\n``divmod(x, y) == (x/y, x%y)``.  These identities don\'t hold for\nfloating point numbers; there similar identities hold approximately\nwhere ``x/y`` is replaced by ``floor(x/y)`` or ``floor(x/y) - 1`` [3].\n\nIn addition to performing the modulo operation on numbers, the ``%``\noperator is also overloaded by string and unicode objects to perform\nstring formatting (also known as interpolation). The syntax for string\nformatting is described in the Python Library Reference, section\n*String Formatting Operations*.\n\nDeprecated since version 2.3: The floor division operator, the modulo\noperator, and the ``divmod()`` function are no longer defined for\ncomplex numbers.  Instead, convert to a floating point number using\nthe ``abs()`` function if appropriate.\n\nThe ``+`` (addition) operator yields the sum of its arguments. The\narguments must either both be numbers or both sequences of the same\ntype.  In the former case, the numbers are converted to a common type\nand then added together.  In the latter case, the sequences are\nconcatenated.\n\nThe ``-`` (subtraction) operator yields the difference of its\narguments.  The numeric arguments are first converted to a common\ntype.\n',
@@ -20,7 +20,7 @@ topics = {'assert': u'\nThe ``assert`` statement\n************************\n\nAs
  'class': u'\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n   classdef    ::= "class" classname [inheritance] ":" suite\n   inheritance ::= "(" [expression_list] ")"\n   classname   ::= identifier\n\nA class definition is an executable statement.  It first evaluates the\ninheritance list, if present.  Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing.  The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.)  When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary.  The class name is bound to this class object in the\noriginal local namespace.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by all instances.  To create instance\nvariables, they can be set in a method with ``self.name = value``.\nBoth class and instance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results.  For *new-style class*es, descriptors can\nbe used to create instance variables with different implementation\ndetails.\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions.  The evaluation rules for the decorator\nexpressions are the same as for functions.  The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n    is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n    exception or the execution of a ``return``, ``continue``, or\n    ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n    body is transformed into the function\'s ``__doc__`` attribute and\n    therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n    body is transformed into the namespace\'s ``__doc__`` item and\n    therefore the class\'s *docstring*.\n',
  'coercion-rules': u"\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 it.  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",
  'comparisons': u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation.  Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n   comparison    ::= or_expr ( comp_operator or_expr )*\n   comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="\n                     | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe forms ``<>`` and ``!=`` are equivalent; for consistency with C,\n``!=`` is preferred; where ``!=`` is mentioned below ``<>`` is also\naccepted.  The ``<>`` spelling is considered obsolescent.\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects.  The objects need not have the same type.\nIf both are numbers, they are converted to a common type.  Otherwise,\nobjects of different types *always* compare unequal, and are ordered\nconsistently but arbitrarily. You can control comparison behavior of\nobjects of non-builtin types by defining a ``__cmp__`` method or rich\ncomparison methods like ``__gt__``, described in section *Special\nmethod names*.\n\n(This unusual definition of comparison was used to simplify the\ndefinition of operations like sorting and the ``in`` and ``not in``\noperators. In the future, the comparison rules for objects of\ndifferent types are likely to change.)\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  Unicode and 8-bit strings are fully interoperable in this behavior.\n  [4]\n\n* Tuples and lists are compared lexicographically using comparison of\n  corresponding elements.  This means that to compare equal, each\n  element must compare equal and the two sequences must be of the same\n  type and have the same length.\n\n  If not equal, the sequences are ordered the same as their first\n  differing elements.  For example, ``cmp([1,2,x], [1,2,y])`` returns\n  the same as ``cmp(x,y)``.  If the corresponding element does not\n  exist, the shorter sequence is ordered first (for example, ``[1,2] <\n  [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if their sorted\n  (key, value) lists compare equal. [5] Outcomes other than equality\n  are resolved consistently, but are not otherwise defined. [6]\n\n* Most other objects of builtin types compare unequal unless they are\n  the same object; the choice whether one object is considered smaller\n  or larger than another one is made arbitrarily but consistently\n  within one execution of a program.\n\nThe operators ``in`` and ``not in`` test for collection membership.\n``x in s`` evaluates to true if *x* is a member of the collection *s*,\nand false otherwise.  ``x not in s`` returns the negation of ``x in\ns``. The collection membership test has traditionally been bound to\nsequences; an object is a member of a collection if the collection is\na sequence and contains an element equal to that object.  However, it\nmake sense for many other object types to support membership tests\nwithout being a sequence.  In particular, dictionaries (for keys) and\nsets support membership testing.\n\nFor the list and tuple types, ``x in y`` is true if and only if there\nexists an index *i* such that ``x == y[i]`` is true.\n\nFor the Unicode and string types, ``x in y`` is true if and only if\n*x* is a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nNote, *x* and *y* need not be the same type; consequently, ``u\'ab\' in\n\'abc\'`` will return ``True``. Empty strings are always considered to\nbe a substring of any other string, so ``"" in "abc"`` will return\n``True``.\n\nChanged in version 2.3: Previously, *x* was required to be a string of\nlength ``1``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` and do\ndefine ``__getitem__()``, ``x in y`` is true if and only if there is a\nnon-negative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object.  ``x is\nnot y`` yields the inverse truth value. [7]\n',
- 'compound': u'\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way.  In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs.  ``try`` specifies exception handlers and/or\ncleanup code for a group of statements.  Function and class\ndefinitions are also syntactically compound statements.\n\nCompound statements consist of one or more \'clauses.\'  A clause\nconsists of a header and a \'suite.\'  The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon.  A suite is a group of statements controlled by a\nclause.  A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines.  Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n   if test1: if test2: print x\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print`` statements are executed:\n\n   if x < y < z: print x; print y; print z\n\nSummarizing:\n\n   compound_stmt ::= if_stmt\n                     | while_stmt\n                     | for_stmt\n                     | try_stmt\n                     | with_stmt\n                     | funcdef\n                     | classdef\n                     | decorated\n   suite         ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n   statement     ::= stmt_list NEWLINE | compound_stmt\n   stmt_list     ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n   if_stmt ::= "if" expression ":" suite\n               ( "elif" expression ":" suite )*\n               ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n   while_stmt ::= "while" expression ":" suite\n                  ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite.  A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n   for_stmt ::= "for" target_list "in" expression_list ":" suite\n                ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject.  An iterator is created for the result of the\n``expression_list``.  The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices.  Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments, and then the suite is executed.  When the items are\nexhausted (which is immediately when the sequence is empty), the suite\nin the ``else`` clause, if present, is executed, and the loop\nterminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite.  A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nThe target list is not deleted when the loop is finished, but if the\nsequence is empty, it will not have been assigned to at all by the\nloop.  Hint: the built-in function ``range()`` returns a sequence of\nintegers suitable to emulate the effect of Pascal\'s ``for i := a to b\ndo``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\nWarning: There is a subtlety when the sequence is being modified by the loop\n  (this can only occur for mutable sequences, i.e. lists). An internal\n  counter is used to keep track of which item is used next, and this\n  is incremented on each iteration.  When this counter has reached the\n  length of the sequence the loop terminates.  This means that if the\n  suite deletes the current (or a previous) item from the sequence,\n  the next item will be skipped (since it gets the index of the\n  current item which has already been treated).  Likewise, if the\n  suite inserts an item in the sequence before the current item, the\n  current item will be treated again the next time through the loop.\n  This can lead to nasty bugs that can be avoided by making a\n  temporary copy using a slice of the whole sequence, e.g.,\n\n   for x in a[:]:\n       if x < 0: a.remove(x)\n\n\nThe ``try`` statement\n=====================\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n   try_stmt  ::= try1_stmt | try2_stmt\n   try1_stmt ::= "try" ":" suite\n                 ("except" [expression ["," target]] ":" suite)+\n                 ["else" ":" suite]\n                 ["finally" ":" suite]\n   try2_stmt ::= "try" ":" suite\n                 "finally" ":" suite\n\nChanged in version 2.5: In previous versions of Python,\n``try``...``except``...``finally`` did not work. ``try``...``except``\nhad to be nested in ``try``...``finally``.\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started.  This search inspects the except\nclauses in turn until one is found that matches the exception.  An\nexpression-less except clause, if present, must be last; it matches\nany exception.  For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception.  An object is\ncompatible with an exception if it is the class or a base class of the\nexception object, a tuple containing an item compatible with the\nexception, or, in the (deprecated) case of string exceptions, is the\nraised string itself (note that the object identities must match, i.e.\nit must be the same string object, not just a string with the same\nvalue).\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified in that except clause, if present, and the except\nclause\'s suite is executed.  All except clauses must have an\nexecutable block.  When the end of this block is reached, execution\ncontinues normally after the entire try statement.  (This means that\nif two nested handlers exist for the same exception, and the exception\noccurs in the try clause of the inner handler, the outer handler will\nnot handle the exception.)\n\nBefore an except clause\'s suite is executed, details about the\nexception are assigned to three variables in the ``sys`` module:\n``sys.exc_type`` receives the object identifying the exception;\n``sys.exc_value`` receives the exception\'s parameter;\n``sys.exc_traceback`` receives a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. These details are also available through the\n``sys.exc_info()`` function, which returns a tuple ``(exc_type,\nexc_value, exc_traceback)``.  Use of the corresponding variables is\ndeprecated in favor of this function, since their use is unsafe in a\nthreaded program.  As of Python 1.5, the variables are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler.  The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses.  If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted.  If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost.  The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nNew in version 2.5.\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n   with_stmt ::= "with" expression ["as" target] ":" suite\n\nThe execution of the ``with`` statement proceeds as follows:\n\n1. The context expression is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__enter__()`` method is invoked.\n\n3. If a target was included in the ``with`` statement, the return\n   value from ``__enter__()`` is assigned to it.\n\n   Note: The ``with`` statement guarantees that if the ``__enter__()``\n     method returns without an error, then ``__exit__()`` will always\n     be called. Thus, if an error occurs during the assignment to the\n     target list, it will be treated the same as an error occurring\n     within the suite would be. See step 5 below.\n\n4. The suite is executed.\n\n5. The context manager\'s ``__exit__()`` method is invoked. If an\n   exception caused the suite to be exited, its type, value, and\n   traceback are passed as arguments to ``__exit__()``. Otherwise,\n   three ``None`` arguments are supplied.\n\n   If the suite was exited due to an exception, and the return value\n   from the ``__exit__()`` method was false, the exception is\n   reraised. If the return value was true, the exception is\n   suppressed, and execution continues with the statement following\n   the ``with`` statement.\n\n   If the suite was exited for any reason other than an exception, the\n   return value from ``__exit__()`` is ignored, and execution proceeds\n   at the normal location for the kind of exit that was taken.\n\nNote: In Python 2.5, the ``with`` statement is only allowed when the\n  ``with_statement`` feature has been enabled.  It is always enabled\n  in Python 2.6.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n   decorated      ::= decorators (classdef | funcdef)\n   decorators     ::= decorator+\n   decorator      ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n   funcdef        ::= "def" funcname "(" [parameter_list] ")" ":" suite\n   dotted_name    ::= identifier ("." identifier)*\n   parameter_list ::= (defparameter ",")*\n                      (  "*" identifier [, "**" identifier]\n                      | "**" identifier\n                      | defparameter [","] )\n   defparameter   ::= parameter ["=" expression]\n   sublist        ::= parameter ("," parameter)* [","]\n   parameter      ::= identifier | "(" sublist ")"\n   funcname       ::= identifier\n\nA function definition is an executable statement.  Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function).  This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition.  The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object.  Multiple decorators are applied in\nnested fashion. For example, the following code:\n\n   @f1(arg)\n   @f2\n   def func(): pass\n\nis equivalent to:\n\n   def func(): pass\n   func = f1(arg)(f2(func))\n\nWhen one or more top-level parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted.  If a parameter has a default value, all following\nparameters must also have a default value --- this is a syntactic\nrestriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.**  This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call.  This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended.  A way around this  is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n   def whats_on_the_telly(penguin=None):\n       if penguin is None:\n           penguin = []\n       penguin.append("property of the zoo")\n       return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values.  If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple.  If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions.  This uses lambda forms,\ndescribed in section *Expression lists*.  Note that the lambda form is\nmerely a shorthand for a simplified function definition; a function\ndefined in a "``def``" statement can be passed around or assigned to\nanother name just like a function defined by a lambda form.  The\n"``def``" form is actually more powerful since it allows the execution\nof multiple statements.\n\n**Programmer\'s note:** Functions are first-class objects.  A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around.  Free variables used in the\nnested function can access the local variables of the function\ncontaining the def.  See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n   classdef    ::= "class" classname [inheritance] ":" suite\n   inheritance ::= "(" [expression_list] ")"\n   classname   ::= identifier\n\nA class definition is an executable statement.  It first evaluates the\ninheritance list, if present.  Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing.  The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.)  When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary.  The class name is bound to this class object in the\noriginal local namespace.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by all instances.  To create instance\nvariables, they can be set in a method with ``self.name = value``.\nBoth class and instance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results.  For *new-style class*es, descriptors can\nbe used to create instance variables with different implementation\ndetails.\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions.  The evaluation rules for the decorator\nexpressions are the same as for functions.  The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n    is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n    exception or the execution of a ``return``, ``continue``, or\n    ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n    body is transformed into the function\'s ``__doc__`` attribute and\n    therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n    body is transformed into the namespace\'s ``__doc__`` item and\n    therefore the class\'s *docstring*.\n',
+ 'compound': u'\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way.  In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs.  ``try`` specifies exception handlers and/or\ncleanup code for a group of statements.  Function and class\ndefinitions are also syntactically compound statements.\n\nCompound statements consist of one or more \'clauses.\'  A clause\nconsists of a header and a \'suite.\'  The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon.  A suite is a group of statements controlled by a\nclause.  A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines.  Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n   if test1: if test2: print x\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print`` statements are executed:\n\n   if x < y < z: print x; print y; print z\n\nSummarizing:\n\n   compound_stmt ::= if_stmt\n                     | while_stmt\n                     | for_stmt\n                     | try_stmt\n                     | with_stmt\n                     | funcdef\n                     | classdef\n                     | decorated\n   suite         ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n   statement     ::= stmt_list NEWLINE | compound_stmt\n   stmt_list     ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n   if_stmt ::= "if" expression ":" suite\n               ( "elif" expression ":" suite )*\n               ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n   while_stmt ::= "while" expression ":" suite\n                  ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite.  A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n   for_stmt ::= "for" target_list "in" expression_list ":" suite\n                ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject.  An iterator is created for the result of the\n``expression_list``.  The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices.  Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments, and then the suite is executed.  When the items are\nexhausted (which is immediately when the sequence is empty), the suite\nin the ``else`` clause, if present, is executed, and the loop\nterminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite.  A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nThe target list is not deleted when the loop is finished, but if the\nsequence is empty, it will not have been assigned to at all by the\nloop.  Hint: the built-in function ``range()`` returns a sequence of\nintegers suitable to emulate the effect of Pascal\'s ``for i := a to b\ndo``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\nWarning: There is a subtlety when the sequence is being modified by the loop\n  (this can only occur for mutable sequences, i.e. lists). An internal\n  counter is used to keep track of which item is used next, and this\n  is incremented on each iteration.  When this counter has reached the\n  length of the sequence the loop terminates.  This means that if the\n  suite deletes the current (or a previous) item from the sequence,\n  the next item will be skipped (since it gets the index of the\n  current item which has already been treated).  Likewise, if the\n  suite inserts an item in the sequence before the current item, the\n  current item will be treated again the next time through the loop.\n  This can lead to nasty bugs that can be avoided by making a\n  temporary copy using a slice of the whole sequence, e.g.,\n\n   for x in a[:]:\n       if x < 0: a.remove(x)\n\n\nThe ``try`` statement\n=====================\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n   try_stmt  ::= try1_stmt | try2_stmt\n   try1_stmt ::= "try" ":" suite\n                 ("except" [expression [("as" | ",") target]] ":" suite)+\n                 ["else" ":" suite]\n                 ["finally" ":" suite]\n   try2_stmt ::= "try" ":" suite\n                 "finally" ":" suite\n\nChanged in version 2.5: In previous versions of Python,\n``try``...``except``...``finally`` did not work. ``try``...``except``\nhad to be nested in ``try``...``finally``.\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started.  This search inspects the except\nclauses in turn until one is found that matches the exception.  An\nexpression-less except clause, if present, must be last; it matches\nany exception.  For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception.  An object is\ncompatible with an exception if it is the class or a base class of the\nexception object, a tuple containing an item compatible with the\nexception, or, in the (deprecated) case of string exceptions, is the\nraised string itself (note that the object identities must match, i.e.\nit must be the same string object, not just a string with the same\nvalue).\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified in that except clause, if present, and the except\nclause\'s suite is executed.  All except clauses must have an\nexecutable block.  When the end of this block is reached, execution\ncontinues normally after the entire try statement.  (This means that\nif two nested handlers exist for the same exception, and the exception\noccurs in the try clause of the inner handler, the outer handler will\nnot handle the exception.)\n\nBefore an except clause\'s suite is executed, details about the\nexception are assigned to three variables in the ``sys`` module:\n``sys.exc_type`` receives the object identifying the exception;\n``sys.exc_value`` receives the exception\'s parameter;\n``sys.exc_traceback`` receives a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. These details are also available through the\n``sys.exc_info()`` function, which returns a tuple ``(exc_type,\nexc_value, exc_traceback)``.  Use of the corresponding variables is\ndeprecated in favor of this function, since their use is unsafe in a\nthreaded program.  As of Python 1.5, the variables are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler.  The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses.  If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted.  If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost.  The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nNew in version 2.5.\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n   with_stmt ::= "with" expression ["as" target] ":" suite\n\nThe execution of the ``with`` statement proceeds as follows:\n\n1. The context expression is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__enter__()`` method is invoked.\n\n3. If a target was included in the ``with`` statement, the return\n   value from ``__enter__()`` is assigned to it.\n\n   Note: The ``with`` statement guarantees that if the ``__enter__()``\n     method returns without an error, then ``__exit__()`` will always\n     be called. Thus, if an error occurs during the assignment to the\n     target list, it will be treated the same as an error occurring\n     within the suite would be. See step 5 below.\n\n4. The suite is executed.\n\n5. The context manager\'s ``__exit__()`` method is invoked. If an\n   exception caused the suite to be exited, its type, value, and\n   traceback are passed as arguments to ``__exit__()``. Otherwise,\n   three ``None`` arguments are supplied.\n\n   If the suite was exited due to an exception, and the return value\n   from the ``__exit__()`` method was false, the exception is\n   reraised. If the return value was true, the exception is\n   suppressed, and execution continues with the statement following\n   the ``with`` statement.\n\n   If the suite was exited for any reason other than an exception, the\n   return value from ``__exit__()`` is ignored, and execution proceeds\n   at the normal location for the kind of exit that was taken.\n\nNote: In Python 2.5, the ``with`` statement is only allowed when the\n  ``with_statement`` feature has been enabled.  It is always enabled\n  in Python 2.6.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n   decorated      ::= decorators (classdef | funcdef)\n   decorators     ::= decorator+\n   decorator      ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n   funcdef        ::= "def" funcname "(" [parameter_list] ")" ":" suite\n   dotted_name    ::= identifier ("." identifier)*\n   parameter_list ::= (defparameter ",")*\n                      (  "*" identifier [, "**" identifier]\n                      | "**" identifier\n                      | defparameter [","] )\n   defparameter   ::= parameter ["=" expression]\n   sublist        ::= parameter ("," parameter)* [","]\n   parameter      ::= identifier | "(" sublist ")"\n   funcname       ::= identifier\n\nA function definition is an executable statement.  Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function).  This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition.  The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object.  Multiple decorators are applied in\nnested fashion. For example, the following code:\n\n   @f1(arg)\n   @f2\n   def func(): pass\n\nis equivalent to:\n\n   def func(): pass\n   func = f1(arg)(f2(func))\n\nWhen one or more top-level parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted.  If a parameter has a default value, all following\nparameters must also have a default value --- this is a syntactic\nrestriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.**  This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call.  This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended.  A way around this  is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n   def whats_on_the_telly(penguin=None):\n       if penguin is None:\n           penguin = []\n       penguin.append("property of the zoo")\n       return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values.  If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple.  If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions.  This uses lambda forms,\ndescribed in section *Expression lists*.  Note that the lambda form is\nmerely a shorthand for a simplified function definition; a function\ndefined in a "``def``" statement can be passed around or assigned to\nanother name just like a function defined by a lambda form.  The\n"``def``" form is actually more powerful since it allows the execution\nof multiple statements.\n\n**Programmer\'s note:** Functions are first-class objects.  A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around.  Free variables used in the\nnested function can access the local variables of the function\ncontaining the def.  See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n   classdef    ::= "class" classname [inheritance] ":" suite\n   inheritance ::= "(" [expression_list] ")"\n   classname   ::= identifier\n\nA class definition is an executable statement.  It first evaluates the\ninheritance list, if present.  Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing.  The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.)  When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary.  The class name is bound to this class object in the\noriginal local namespace.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by all instances.  To create instance\nvariables, they can be set in a method with ``self.name = value``.\nBoth class and instance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results.  For *new-style class*es, descriptors can\nbe used to create instance variables with different implementation\ndetails.\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions.  The evaluation rules for the decorator\nexpressions are the same as for functions.  The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n    is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n    exception or the execution of a ``return``, ``continue``, or\n    ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n    body is transformed into the function\'s ``__doc__`` attribute and\n    therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n    body is transformed into the namespace\'s ``__doc__`` item and\n    therefore the class\'s *docstring*.\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',
@@ -43,9 +43,9 @@ topics = {'assert': u'\nThe ``assert`` statement\n************************\n\nAs
  'identifiers': u'\nIdentifiers and keywords\n************************\n\nIdentifiers (also referred to as *names*) are described by the\nfollowing lexical definitions:\n\n   identifier ::= (letter|"_") (letter | digit | "_")*\n   letter     ::= lowercase | uppercase\n   lowercase  ::= "a"..."z"\n   uppercase  ::= "A"..."Z"\n   digit      ::= "0"..."9"\n\nIdentifiers are unlimited in length.  Case is significant.\n\n\nKeywords\n========\n\nThe following identifiers are used as reserved words, or *keywords* of\nthe language, and cannot be used as ordinary identifiers.  They must\nbe spelled exactly as written here:\n\n   and       del       from      not       while\n   as        elif      global    or        with\n   assert    else      if        pass      yield\n   break     except    import    print\n   class     exec      in        raise\n   continue  finally   is        return\n   def       for       lambda    try\n\nChanged in version 2.4: ``None`` became a constant and is now\nrecognized by the compiler as a name for the built-in object ``None``.\nAlthough it is not a keyword, you cannot assign a different object to\nit.\n\nChanged in version 2.5: Both ``as`` and ``with`` are only recognized\nwhen the ``with_statement`` future feature has been enabled. It will\nalways be enabled in Python 2.6.  See section *The with statement* for\ndetails.  Note that using ``as`` and ``with`` as identifiers will\nalways issue a warning, even when the ``with_statement`` future\ndirective is not in effect.\n\n\nReserved classes of identifiers\n===============================\n\nCertain classes of identifiers (besides keywords) have special\nmeanings.  These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n   Not imported by ``from module import *``.  The special identifier\n   ``_`` is used in the interactive interpreter to store the result of\n   the last evaluation; it is stored in the ``__builtin__`` module.\n   When not in interactive mode, ``_`` has no special meaning and is\n   not defined. See section *The import statement*.\n\n   Note: The name ``_`` is often used in conjunction with\n     internationalization; refer to the documentation for the\n     ``gettext`` module for more information on this convention.\n\n``__*__``\n   System-defined names.  These names are defined by the interpreter\n   and its implementation (including the standard library);\n   applications should not expect to define additional names using\n   this convention.  The set of names of this class defined by Python\n   may be extended in future versions. See section *Special method\n   names*.\n\n``__*``\n   Class-private names.  Names in this category, when used within the\n   context of a class definition, are re-written to use a mangled form\n   to help avoid name clashes between "private" attributes of base and\n   derived classes. See section *Identifiers (Names)*.\n',
  'if': u'\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n   if_stmt ::= "if" expression ":" suite\n               ( "elif" expression ":" suite )*\n               ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n',
  'imaginary': u'\nImaginary literals\n******************\n\nImaginary literals are described by the following lexical definitions:\n\n   imagnumber ::= (floatnumber | intpart) ("j" | "J")\n\nAn imaginary literal yields a complex number with a real part of 0.0.\nComplex numbers are represented as a pair of floating point numbers\nand have the same restrictions on their range.  To create a complex\nnumber with a nonzero real part, add a floating point number to it,\ne.g., ``(3+4j)``.  Some examples of imaginary literals:\n\n   3.14j   10.j    10j     .001j   1e100j  3.14e-10j\n',
- 'import': u'\nThe ``import`` statement\n************************\n\n   import_stmt     ::= "import" module ["as" name] ( "," module ["as" name] )*\n                   | "from" relative_module "import" identifier ["as" name]\n                   ( "," identifier ["as" name] )*\n                   | "from" relative_module "import" "(" identifier ["as" name]\n                   ( "," identifier ["as" name] )* [","] ")"\n                   | "from" module "import" "*"\n   module          ::= (identifier ".")* identifier\n   relative_module ::= "."* module | "."+\n   name            ::= identifier\n\nImport statements are executed in two steps: (1) find a module, and\ninitialize it if necessary; (2) define a name or names in the local\nnamespace (of the scope where the ``import`` statement occurs). The\nfirst form (without ``from``) repeats these steps for each identifier\nin the list.  The form with ``from`` performs step (1) once, and then\nperforms step (2) repeatedly.\n\nIn this context, to "initialize" a built-in or extension module means\nto call an initialization function that the module must provide for\nthe purpose (in the reference implementation, the function\'s name is\nobtained by prepending string "init" to the module\'s name); to\n"initialize" a Python-coded module means to execute the module\'s body.\n\nThe system maintains a table of modules that have been or are being\ninitialized, indexed by module name.  This table is accessible as\n``sys.modules``.  When a module name is found in this table, step (1)\nis finished.  If not, a search for a module definition is started.\nWhen a module is found, it is loaded.  Details of the module searching\nand loading process are implementation and platform specific.  It\ngenerally involves searching for a "built-in" module with the given\nname and then searching a list of locations given as ``sys.path``.\n\nIf a built-in module is found, its built-in initialization code is\nexecuted and step (1) is finished.  If no matching file is found,\n``ImportError`` is raised. If a file is found, it is parsed, yielding\nan executable code block.  If a syntax error occurs, ``SyntaxError``\nis raised.  Otherwise, an empty module of the given name is created\nand inserted in the module table, and then the code block is executed\nin the context of this module.  Exceptions during this execution\nterminate step (1).\n\nWhen step (1) finishes without raising an exception, step (2) can\nbegin.\n\nThe first form of ``import`` statement binds the module name in the\nlocal namespace to the module object, and then goes on to import the\nnext identifier, if any.  If the module name is followed by ``as``,\nthe name following ``as`` is used as the local name for the module.\n\nThe ``from`` form does not bind the module name: it goes through the\nlist of identifiers, looks each one of them up in the module found in\nstep (1), and binds the name in the local namespace to the object thus\nfound.  As with the first form of ``import``, an alternate local name\ncan be supplied by specifying "``as`` localname".  If a name is not\nfound, ``ImportError`` is raised.  If the list of identifiers is\nreplaced by a star (``\'*\'``), all public names defined in the module\nare bound in the local namespace of the ``import`` statement..\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named ``__all__``; if defined, it\nmust be a sequence of strings which are names defined or imported by\nthat module.  The names given in ``__all__`` are all considered public\nand are required to exist.  If ``__all__`` is not defined, the set of\npublic names includes all names found in the module\'s namespace which\ndo not begin with an underscore character (``\'_\'``). ``__all__``\nshould contain the entire public API. It is intended to avoid\naccidentally exporting items that are not part of the API (such as\nlibrary modules which were imported and used within the module).\n\nThe ``from`` form with ``*`` may only occur in a module scope.  If the\nwild card form of import --- ``import *`` --- is used in a function\nand the function contains or is a nested block with free variables,\nthe compiler will raise a ``SyntaxError``.\n\n**Hierarchical module names:** when the module names contains one or\nmore dots, the module search path is carried out differently.  The\nsequence of identifiers up to the last dot is used to find a\n"package"; the final identifier is then searched inside the package.\nA package is generally a subdirectory of a directory on ``sys.path``\nthat has a file ``__init__.py``.\n\nThe built-in function ``__import__()`` is provided to support\napplications that determine which modules need to be loaded\ndynamically; refer to *Built-in Functions* for additional information.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python.  The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language.  It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n   future_statement ::= "from" "__future__" "import" feature ["as" name]\n                        ("," feature ["as" name])*\n                        | "from" "__future__" "import" "(" feature ["as" name]\n                        ("," feature ["as" name])* [","] ")"\n   feature          ::= identifier\n   name             ::= identifier\n\nA future statement must appear near the top of the module.  The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 2.5 are ``absolute_import``,\n``division``, ``generators``, ``nested_scopes`` and\n``with_statement``.  ``generators`` and ``nested_scopes``  are\nredundant in Python version 2.3 and above because they are always\nenabled.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code.  It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently.  Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n   import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by an ``exec`` statement or calls to the builtin\nfunctions ``compile()`` and ``execfile()`` that occur in a module\n``M`` containing a future statement will, by default, use the new\nsyntax or semantics associated with the future statement.  This can,\nstarting with Python 2.2 be controlled by optional arguments to\n``compile()`` --- see the documentation of that function for details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session.  If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n',
+ 'import': u'\nThe ``import`` statement\n************************\n\n   import_stmt     ::= "import" module ["as" name] ( "," module ["as" name] )*\n                   | "from" relative_module "import" identifier ["as" name]\n                   ( "," identifier ["as" name] )*\n                   | "from" relative_module "import" "(" identifier ["as" name]\n                   ( "," identifier ["as" name] )* [","] ")"\n                   | "from" module "import" "*"\n   module          ::= (identifier ".")* identifier\n   relative_module ::= "."* module | "."+\n   name            ::= identifier\n\nImport statements are executed in two steps: (1) find a module, and\ninitialize it if necessary; (2) define a name or names in the local\nnamespace (of the scope where the ``import`` statement occurs). The\nfirst form (without ``from``) repeats these steps for each identifier\nin the list.  The form with ``from`` performs step (1) once, and then\nperforms step (2) repeatedly.\n\nIn this context, to "initialize" a built-in or extension module means\nto call an initialization function that the module must provide for\nthe purpose (in the reference implementation, the function\'s name is\nobtained by prepending string "init" to the module\'s name); to\n"initialize" a Python-coded module means to execute the module\'s body.\n\nThe system maintains a table of modules that have been or are being\ninitialized, indexed by module name.  This table is accessible as\n``sys.modules``.  When a module name is found in this table, step (1)\nis finished.  If not, a search for a module definition is started.\nWhen a module is found, it is loaded.  Details of the module searching\nand loading process are implementation and platform specific.  It\ngenerally involves searching for a "built-in" module with the given\nname and then searching a list of locations given as ``sys.path``.\n\nIf a built-in module is found, its built-in initialization code is\nexecuted and step (1) is finished.  If no matching file is found,\n``ImportError`` is raised. If a file is found, it is parsed, yielding\nan executable code block.  If a syntax error occurs, ``SyntaxError``\nis raised.  Otherwise, an empty module of the given name is created\nand inserted in the module table, and then the code block is executed\nin the context of this module.  Exceptions during this execution\nterminate step (1).\n\nWhen step (1) finishes without raising an exception, step (2) can\nbegin.\n\nThe first form of ``import`` statement binds the module name in the\nlocal namespace to the module object, and then goes on to import the\nnext identifier, if any.  If the module name is followed by ``as``,\nthe name following ``as`` is used as the local name for the module.\n\nThe ``from`` form does not bind the module name: it goes through the\nlist of identifiers, looks each one of them up in the module found in\nstep (1), and binds the name in the local namespace to the object thus\nfound.  As with the first form of ``import``, an alternate local name\ncan be supplied by specifying "``as`` localname".  If a name is not\nfound, ``ImportError`` is raised.  If the list of identifiers is\nreplaced by a star (``\'*\'``), all public names defined in the module\nare bound in the local namespace of the ``import`` statement..\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named ``__all__``; if defined, it\nmust be a sequence of strings which are names defined or imported by\nthat module.  The names given in ``__all__`` are all considered public\nand are required to exist.  If ``__all__`` is not defined, the set of\npublic names includes all names found in the module\'s namespace which\ndo not begin with an underscore character (``\'_\'``). ``__all__``\nshould contain the entire public API. It is intended to avoid\naccidentally exporting items that are not part of the API (such as\nlibrary modules which were imported and used within the module).\n\nThe ``from`` form with ``*`` may only occur in a module scope.  If the\nwild card form of import --- ``import *`` --- is used in a function\nand the function contains or is a nested block with free variables,\nthe compiler will raise a ``SyntaxError``.\n\n**Hierarchical module names:** when the module names contains one or\nmore dots, the module search path is carried out differently.  The\nsequence of identifiers up to the last dot is used to find a\n"package"; the final identifier is then searched inside the package.\nA package is generally a subdirectory of a directory on ``sys.path``\nthat has a file ``__init__.py``.\n\nThe built-in function ``__import__()`` is provided to support\napplications that determine which modules need to be loaded\ndynamically; refer to *Built-in Functions* for additional information.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python.  The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language.  It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n   future_statement ::= "from" "__future__" "import" feature ["as" name]\n                        ("," feature ["as" name])*\n                        | "from" "__future__" "import" "(" feature ["as" name]\n                        ("," feature ["as" name])* [","] ")"\n   feature          ::= identifier\n   name             ::= identifier\n\nA future statement must appear near the top of the module.  The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 2.6 are ``unicode_literals``,\n``print_function``, ``absolute_import``, ``division``, ``generators``,\n``nested_scopes`` and ``with_statement``.  ``generators``,\n``with_statement``, ``nested_scopes`` are redundant in Python version\n2.6 and above because they are always enabled.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code.  It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently.  Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n   import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by an ``exec`` statement or calls to the builtin\nfunctions ``compile()`` and ``execfile()`` that occur in a module\n``M`` containing a future statement will, by default, use the new\nsyntax or semantics associated with the future statement.  This can,\nstarting with Python 2.2 be controlled by optional arguments to\n``compile()`` --- see the documentation of that function for details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session.  If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n',
  'in': u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation.  Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n   comparison    ::= or_expr ( comp_operator or_expr )*\n   comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="\n                     | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe forms ``<>`` and ``!=`` are equivalent; for consistency with C,\n``!=`` is preferred; where ``!=`` is mentioned below ``<>`` is also\naccepted.  The ``<>`` spelling is considered obsolescent.\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects.  The objects need not have the same type.\nIf both are numbers, they are converted to a common type.  Otherwise,\nobjects of different types *always* compare unequal, and are ordered\nconsistently but arbitrarily. You can control comparison behavior of\nobjects of non-builtin types by defining a ``__cmp__`` method or rich\ncomparison methods like ``__gt__``, described in section *Special\nmethod names*.\n\n(This unusual definition of comparison was used to simplify the\ndefinition of operations like sorting and the ``in`` and ``not in``\noperators. In the future, the comparison rules for objects of\ndifferent types are likely to change.)\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  Unicode and 8-bit strings are fully interoperable in this behavior.\n  [4]\n\n* Tuples and lists are compared lexicographically using comparison of\n  corresponding elements.  This means that to compare equal, each\n  element must compare equal and the two sequences must be of the same\n  type and have the same length.\n\n  If not equal, the sequences are ordered the same as their first\n  differing elements.  For example, ``cmp([1,2,x], [1,2,y])`` returns\n  the same as ``cmp(x,y)``.  If the corresponding element does not\n  exist, the shorter sequence is ordered first (for example, ``[1,2] <\n  [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if their sorted\n  (key, value) lists compare equal. [5] Outcomes other than equality\n  are resolved consistently, but are not otherwise defined. [6]\n\n* Most other objects of builtin types compare unequal unless they are\n  the same object; the choice whether one object is considered smaller\n  or larger than another one is made arbitrarily but consistently\n  within one execution of a program.\n\nThe operators ``in`` and ``not in`` test for collection membership.\n``x in s`` evaluates to true if *x* is a member of the collection *s*,\nand false otherwise.  ``x not in s`` returns the negation of ``x in\ns``. The collection membership test has traditionally been bound to\nsequences; an object is a member of a collection if the collection is\na sequence and contains an element equal to that object.  However, it\nmake sense for many other object types to support membership tests\nwithout being a sequence.  In particular, dictionaries (for keys) and\nsets support membership testing.\n\nFor the list and tuple types, ``x in y`` is true if and only if there\nexists an index *i* such that ``x == y[i]`` is true.\n\nFor the Unicode and string types, ``x in y`` is true if and only if\n*x* is a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nNote, *x* and *y* need not be the same type; consequently, ``u\'ab\' in\n\'abc\'`` will return ``True``. Empty strings are always considered to\nbe a substring of any other string, so ``"" in "abc"`` will return\n``True``.\n\nChanged in version 2.3: Previously, *x* was required to be a string of\nlength ``1``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` and do\ndefine ``__getitem__()``, ``x in y`` is true if and only if there is a\nnon-negative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object.  ``x is\nnot y`` yields the inverse truth value. [7]\n',
- 'integers': u'\nInteger and long integer literals\n*********************************\n\nInteger and long integer literals are described by the following\nlexical definitions:\n\n   longinteger    ::= integer ("l" | "L")\n   integer        ::= decimalinteger | octinteger | hexinteger\n   decimalinteger ::= nonzerodigit digit* | "0"\n   octinteger     ::= "0" octdigit+\n   hexinteger     ::= "0" ("x" | "X") hexdigit+\n   nonzerodigit   ::= "1"..."9"\n   octdigit       ::= "0"..."7"\n   hexdigit       ::= digit | "a"..."f" | "A"..."F"\n\nAlthough both lower case ``\'l\'`` and upper case ``\'L\'`` are allowed as\nsuffix for long integers, it is strongly recommended to always use\n``\'L\'``, since the letter ``\'l\'`` looks too much like the digit\n``\'1\'``.\n\nPlain integer literals that are above the largest representable plain\ninteger (e.g., 2147483647 when using 32-bit arithmetic) are accepted\nas if they were long integers instead. [1]  There is no limit for long\ninteger literals apart from what can be stored in available memory.\n\nSome examples of plain integer literals (first row) and long integer\nliterals (second and third rows):\n\n   7     2147483647                        0177\n   3L    79228162514264337593543950336L    0377L   0x100000000L\n         79228162514264337593543950336             0xdeadbeef\n',
+ 'integers': u'\nInteger and long integer literals\n*********************************\n\nInteger and long integer literals are described by the following\nlexical definitions:\n\n   longinteger    ::= integer ("l" | "L")\n   integer        ::= decimalinteger | octinteger | hexinteger | bininteger\n   decimalinteger ::= nonzerodigit digit* | "0"\n   octinteger     ::= "0" ("o" | "O") octdigit+ | "0" octdigit+\n   hexinteger     ::= "0" ("x" | "X") hexdigit+\n   bininteger     ::= "0" ("b" | "B") bindigit+\n   nonzerodigit   ::= "1"..."9"\n   octdigit       ::= "0"..."7"\n   bindigit       ::= "0" | "1"\n   hexdigit       ::= digit | "a"..."f" | "A"..."F"\n\nAlthough both lower case ``\'l\'`` and upper case ``\'L\'`` are allowed as\nsuffix for long integers, it is strongly recommended to always use\n``\'L\'``, since the letter ``\'l\'`` looks too much like the digit\n``\'1\'``.\n\nPlain integer literals that are above the largest representable plain\ninteger (e.g., 2147483647 when using 32-bit arithmetic) are accepted\nas if they were long integers instead. [1]  There is no limit for long\ninteger literals apart from what can be stored in available memory.\n\nSome examples of plain integer literals (first row) and long integer\nliterals (second and third rows):\n\n   7     2147483647                        0177\n   3L    79228162514264337593543950336L    0377L   0x100000000L\n         79228162514264337593543950336             0xdeadbeef\n',
  'lambda': u'\nExpression lists\n****************\n\n   expression_list ::= expression ( "," expression )* [","]\n\nAn expression list containing at least one comma yields a tuple.  The\nlength of the tuple is the number of expressions in the list.  The\nexpressions are evaluated from left to right.\n\nThe trailing comma is required only to create a single tuple (a.k.a. a\n*singleton*); it is optional in all other cases.  A single expression\nwithout a trailing comma doesn\'t create a tuple, but rather yields the\nvalue of that expression. (To create an empty tuple, use an empty pair\nof parentheses: ``()``.)\n',
  'lists': u'\nList displays\n*************\n\nA list display is a possibly empty series of expressions enclosed in\nsquare brackets:\n\n   list_display        ::= "[" [expression_list | list_comprehension] "]"\n   list_comprehension  ::= expression list_for\n   list_for            ::= "for" target_list "in" old_expression_list [list_iter]\n   old_expression_list ::= old_expression [("," old_expression)+ [","]]\n   list_iter           ::= list_for | list_if\n   list_if             ::= "if" old_expression [list_iter]\n\nA list display yields a new list object.  Its contents are specified\nby providing either a list of expressions or a list comprehension.\nWhen a comma-separated list of expressions is supplied, its elements\nare evaluated from left to right and placed into the list object in\nthat order.  When a list comprehension is supplied, it consists of a\nsingle expression followed by at least one ``for`` clause and zero or\nmore ``for`` or ``if`` clauses.  In this case, the elements of the new\nlist are those that would be produced by considering each of the\n``for`` or ``if`` clauses a block, nesting from left to right, and\nevaluating the expression to produce a list element each time the\ninnermost block is reached [1].\n',
  'naming': u'\nNaming and binding\n******************\n\n*Names* refer to objects.  Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block.  A script\nfile (a file given as standard input to the interpreter or specified\non the interpreter command line the first argument) is a code block.\nA script command (a command specified on the interpreter command line\nwith the \'**-c**\' option) is a code block.  The file read by the\nbuilt-in function ``execfile()`` is a code block.  The string argument\npassed to the built-in function ``eval()`` and to the ``exec``\nstatement is a code block. The expression read and evaluated by the\nbuilt-in function ``input()`` is a code block.\n\nA code block is executed in an *execution frame*.  A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block.  If a local\nvariable is defined in a block, its scope includes that block.  If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name.  The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes generator expressions since\nthey are implemented using a function scope.  This means that the\nfollowing will fail:\n\n   class A:\n       a = 42\n       b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope.  The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nIf a name is bound in a block, it is a local variable of that block.\nIf a name is bound at the module level, it is a global variable.  (The\nvariables of the module code block are local and global.)  If a\nvariable is used in a code block but not defined there, it is a *free\nvariable*.\n\nWhen a name is not found at all, a ``NameError`` exception is raised.\nIf the name refers to a local variable that has not been bound, a\n``UnboundLocalError`` exception is raised.  ``UnboundLocalError`` is a\nsubclass of ``NameError``.\n\nThe following constructs bind names: formal parameters to functions,\n``import`` statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, ``for`` loop header, or in\nthe second position of an ``except`` clause header.  The ``import``\nstatement of the form "``from ...import *``" binds all names defined\nin the imported module, except those beginning with an underscore.\nThis form may only be used at the module level.\n\nA target occurring in a ``del`` statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name).  It\nis illegal to unbind a name that is referenced by an enclosing scope;\nthe compiler will report a ``SyntaxError``.\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block.  This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle.  Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block.  The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the global statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtin namespace, the namespace of\nthe module ``__builtin__``.  The global namespace is searched first.\nIf the name is not found there, the builtin namespace is searched.\nThe global statement must precede all uses of the name.\n\nThe built-in namespace associated with the execution of a code block\nis actually found by looking up the name ``__builtins__`` in its\nglobal namespace; this should be a dictionary or a module (in the\nlatter case the module\'s dictionary is used).  By default, when in the\n``__main__`` module, ``__builtins__`` is the built-in module\n``__builtin__`` (note: no \'s\'); when in any other module,\n``__builtins__`` is an alias for the dictionary of the ``__builtin__``\nmodule itself.  ``__builtins__`` can be set to a user-created\ndictionary to create a weak form of restricted execution.\n\nNote: Users should not touch ``__builtins__``; it is strictly an\n  implementation detail.  Users wanting to override values in the\n  built-in namespace should ``import`` the ``__builtin__`` (no \'s\')\n  module and modify its attributes appropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported.  The main module for a script is always called\n``__main__``.\n\nThe global statement has the same scope as a name binding operation in\nthe same block.  If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class.  Names defined at the class scope are not visible in\nmethods.\n\n\nInteraction with dynamic features\n=================================\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name.  An error will be reported at compile time.\n\nIf the wild card form of import --- ``import *`` --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a ``SyntaxError``.\n\nIf ``exec`` is used in a function and the function contains or is a\nnested block with free variables, the compiler will raise a\n``SyntaxError`` unless the exec explicitly specifies the local\nnamespace for the ``exec``.  (In other words, ``exec obj`` would be\nillegal, but ``exec obj in ns`` would be legal.)\n\nThe ``eval()``, ``execfile()``, and ``input()`` functions and the\n``exec`` statement do not have access to the full environment for\nresolving names.  Names may be resolved in the local and global\nnamespaces of the caller.  Free variables are not resolved in the\nnearest enclosing namespace, but in the global namespace. [1] The\n``exec`` statement and the ``eval()`` and ``execfile()`` functions\nhave optional arguments to override the global and local namespace.\nIf only one namespace is specified, it is used for both.\n',
@@ -63,16 +63,16 @@ topics = {'assert': u'\nThe ``assert`` statement\n************************\n\nAs
  '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.  If there are no base\n   classes, this will be an empty tuple.\n\nclass.__name__\n\n   The name of the class or type.\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.  For this reason, ``__del__()`` methods should do\n     the absolute minimum needed to maintain external invariants.\n     Starting with version 1.5, Python guarantees that globals whose\n     name begins with a single underscore are deleted from their\n     module before other globals are deleted; if no other references\n     to such globals exist, this may help in assuring that imported\n     modules are still available at the time when the ``__del__()``\n     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\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 for the key object for dictionary operations, and by the\n   built-in function ``hash()``.  Should return an integer usable as a\n   hash value for dictionary operations.  The only required property\n   is that objects which compare equal have the same hash value; it is\n   advised to somehow mix together (e.g., using exclusive or) the hash\n   values for the components of the object that also play a part in\n   comparison of objects.\n\n   If a class does not define a ``__cmp__()`` or ``__eq__()`` method\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 as dictionary keys.  If a class\n   defines mutable objects and implements a ``__cmp__()`` or\n   ``__eq__()`` method, it should not implement ``__hash__()``, since\n   the dictionary implementation requires that a key\'s hash value is\n   immutable (if the object\'s hash value changes, it will be in the\n   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 (see below).  If a class\n   defines neither ``__len__()`` nor ``__nonzero__()``, all its\n   instances are considered true.\n\nobject.__unicode__(self)\n\n   Called to implement ``unicode()`` builtin; 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     builtin 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.  Normally, data\ndescriptors define both ``__get__()`` and ``__set__()``, while non-\ndata descriptors have just the ``__get__()`` method.  Data descriptors\nalways override a redefinition in an instance dictionary.  In\ncontrast, non-data descriptors can be overridden by instances. [2]\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* 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* 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__*.\n\n* *__slots__* do not work for classes derived from "variable-length"\n  built-in types such as ``long``, ``str`` and ``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\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()`` builtin 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()`` builtin will fall back to using the sequence\n   protocol (``__len__()`` and ``__getitem__()``).  Objects should\n   normally only provide ``__reversed__()`` if they do not support the\n   sequence protocol and an efficient implementation of reverse\n   iteration is possible.\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\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. [3] 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   operations (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\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   operation falls back to the normal methods.  For instance, to\n   evaluate the expression ``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 it.  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 may also bypass the\n``__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] A descriptor can define any combination of ``__get__()``,\n    ``__set__()`` and ``__delete__()``.  If it does not define\n    ``__get__()``, then accessing the attribute even on an instance\n    will return the descriptor object itself.  If the descriptor\n    defines ``__set__()`` and/or ``__delete__()``, it is a data\n    descriptor; if it defines neither, it is a non-data descriptor.\n\n[3] 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.  For this reason, ``__del__()`` methods should do\n     the absolute minimum needed to maintain external invariants.\n     Starting with version 1.5, Python guarantees that globals whose\n     name begins with a single underscore are deleted from their\n     module before other globals are deleted; if no other references\n     to such globals exist, this may help in assuring that imported\n     modules are still available at the time when the ``__del__()``\n     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\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 for the key object for dictionary operations, and by the\n   built-in function ``hash()``.  Should return an integer usable as a\n   hash value for dictionary operations.  The only required property\n   is that objects which compare equal have the same hash value; it is\n   advised to somehow mix together (e.g., using exclusive or) the hash\n   values for the components of the object that also play a part in\n   comparison of objects.\n\n   If a class does not define a ``__cmp__()`` or ``__eq__()`` method\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 as dictionary keys.  If a class\n   defines mutable objects and implements a ``__cmp__()`` or\n   ``__eq__()`` method, it should not implement ``__hash__()``, since\n   the dictionary implementation requires that a key\'s hash value is\n   immutable (if the object\'s hash value changes, it will be in the\n   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 (see below).  If a class\n   defines neither ``__len__()`` nor ``__nonzero__()``, all its\n   instances are considered true.\n\nobject.__unicode__(self)\n\n   Called to implement ``unicode()`` builtin; 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     builtin 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.  Normally, data\ndescriptors define both ``__get__()`` and ``__set__()``, while non-\ndata descriptors have just the ``__get__()`` method.  Data descriptors\nalways override a redefinition in an instance dictionary.  In\ncontrast, non-data descriptors can be overridden by instances. [2]\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* 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* 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__*.\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\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()`` builtin 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()`` builtin will fall back to using the sequence\n   protocol (``__len__()`` and ``__getitem__()``).  Objects should\n   normally only provide ``__reversed__()`` if they do not support the\n   sequence protocol and an efficient implementation of reverse\n   iteration is possible.\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\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. [3] 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   operations (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\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   operation falls back to the normal methods.  For instance, to\n   evaluate the expression ``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 it.  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 may also bypass the\n``__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] A descriptor can define any combination of ``__get__()``,\n    ``__set__()`` and ``__delete__()``.  If it does not define\n    ``__get__()``, then accessing the attribute even on an instance\n    will return the descriptor object itself.  If the descriptor\n    defines ``__set__()`` and/or ``__delete__()``, it is a data\n    descriptor; if it defines neither, it is a non-data descriptor.\n\n[3] 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 only its first character\n   capitalized.\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 occurrences of substring *sub* in the range\n   [*start*, *end*].  Optional arguments *start* and *end* are\n   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 range [*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(format_string, *args, **kwargs)\n\n   Perform a string formatting operation.  The *format_string*\n   argument can contain literal text or replacement fields delimited\n   by braces ``{}``.  Each replacement field contains either the\n   numeric index of a positional argument, or the name of a keyword\n   argument.  Returns a copy of *format_string* where each replacement\n   field is replaced with the string value of the corresponding\n   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(seq)\n\n   Return a string which is the concatenation of the strings in the\n   sequence *seq*. The separator between elements is the string\n   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].  Optional\n   arguments *start* and *end* are interpreted as in slice notation.\n   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: words start with\n   uppercase characters, all remaining cased characters are lowercase.\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',
  'subscriptions': u'\nSubscriptions\n*************\n\nA subscription selects an item of a sequence (string, tuple or list)\nor mapping (dictionary) object:\n\n   subscription ::= primary "[" expression_list "]"\n\nThe primary must evaluate to an object of a sequence or mapping type.\n\nIf the primary is a mapping, the expression list must evaluate to an\nobject whose value is one of the keys of the mapping, and the\nsubscription selects the value in the mapping that corresponds to that\nkey.  (The expression list is a tuple except if it has exactly one\nitem.)\n\nIf the primary is a sequence, the expression (list) must evaluate to a\nplain integer.  If this value is negative, the length of the sequence\nis added to it (so that, e.g., ``x[-1]`` selects the last item of\n``x``.)  The resulting value must be a nonnegative integer less than\nthe number of items in the sequence, and the subscription selects the\nitem whose index is that value (counting from zero).\n\nA string\'s items are characters.  A character is not a separate data\ntype but a string of exactly one character.\n',
  'truth': u"\nTruth Value Testing\n*******************\n\nAny object can be tested for truth value, for use in an ``if`` or\n``while`` condition or as operand of the Boolean operations below. The\nfollowing values are considered false:\n\n* ``None``\n\n* ``False``\n\n* zero of any numeric type, for example, ``0``, ``0L``, ``0.0``,\n  ``0j``.\n\n* any empty sequence, for example, ``''``, ``()``, ``[]``.\n\n* any empty mapping, for example, ``{}``.\n\n* instances of user-defined classes, if the class defines a\n  ``__nonzero__()`` or ``__len__()`` method, when that method returns\n  the integer zero or ``bool`` value ``False``. [1]\n\nAll other values are considered true --- so objects of many types are\nalways true.\n\nOperations and built-in functions that have a Boolean result always\nreturn ``0`` or ``False`` for false and ``1`` or ``True`` for true,\nunless otherwise stated. (Important exception: the Boolean operations\n``or`` and ``and`` always return one of their operands.)\n",
- 'try': u'\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n   try_stmt  ::= try1_stmt | try2_stmt\n   try1_stmt ::= "try" ":" suite\n                 ("except" [expression ["," target]] ":" suite)+\n                 ["else" ":" suite]\n                 ["finally" ":" suite]\n   try2_stmt ::= "try" ":" suite\n                 "finally" ":" suite\n\nChanged in version 2.5: In previous versions of Python,\n``try``...``except``...``finally`` did not work. ``try``...``except``\nhad to be nested in ``try``...``finally``.\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started.  This search inspects the except\nclauses in turn until one is found that matches the exception.  An\nexpression-less except clause, if present, must be last; it matches\nany exception.  For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception.  An object is\ncompatible with an exception if it is the class or a base class of the\nexception object, a tuple containing an item compatible with the\nexception, or, in the (deprecated) case of string exceptions, is the\nraised string itself (note that the object identities must match, i.e.\nit must be the same string object, not just a string with the same\nvalue).\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified in that except clause, if present, and the except\nclause\'s suite is executed.  All except clauses must have an\nexecutable block.  When the end of this block is reached, execution\ncontinues normally after the entire try statement.  (This means that\nif two nested handlers exist for the same exception, and the exception\noccurs in the try clause of the inner handler, the outer handler will\nnot handle the exception.)\n\nBefore an except clause\'s suite is executed, details about the\nexception are assigned to three variables in the ``sys`` module:\n``sys.exc_type`` receives the object identifying the exception;\n``sys.exc_value`` receives the exception\'s parameter;\n``sys.exc_traceback`` receives a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. These details are also available through the\n``sys.exc_info()`` function, which returns a tuple ``(exc_type,\nexc_value, exc_traceback)``.  Use of the corresponding variables is\ndeprecated in favor of this function, since their use is unsafe in a\nthreaded program.  As of Python 1.5, the variables are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler.  The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses.  If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted.  If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost.  The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n',
+ 'try': u'\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n   try_stmt  ::= try1_stmt | try2_stmt\n   try1_stmt ::= "try" ":" suite\n                 ("except" [expression [("as" | ",") target]] ":" suite)+\n                 ["else" ":" suite]\n                 ["finally" ":" suite]\n   try2_stmt ::= "try" ":" suite\n                 "finally" ":" suite\n\nChanged in version 2.5: In previous versions of Python,\n``try``...``except``...``finally`` did not work. ``try``...``except``\nhad to be nested in ``try``...``finally``.\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started.  This search inspects the except\nclauses in turn until one is found that matches the exception.  An\nexpression-less except clause, if present, must be last; it matches\nany exception.  For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception.  An object is\ncompatible with an exception if it is the class or a base class of the\nexception object, a tuple containing an item compatible with the\nexception, or, in the (deprecated) case of string exceptions, is the\nraised string itself (note that the object identities must match, i.e.\nit must be the same string object, not just a string with the same\nvalue).\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified in that except clause, if present, and the except\nclause\'s suite is executed.  All except clauses must have an\nexecutable block.  When the end of this block is reached, execution\ncontinues normally after the entire try statement.  (This means that\nif two nested handlers exist for the same exception, and the exception\noccurs in the try clause of the inner handler, the outer handler will\nnot handle the exception.)\n\nBefore an except clause\'s suite is executed, details about the\nexception are assigned to three variables in the ``sys`` module:\n``sys.exc_type`` receives the object identifying the exception;\n``sys.exc_value`` receives the exception\'s parameter;\n``sys.exc_traceback`` receives a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. These details are also available through the\n``sys.exc_info()`` function, which returns a tuple ``(exc_type,\nexc_value, exc_traceback)``.  Use of the corresponding variables is\ndeprecated in favor of this function, since their use is unsafe in a\nthreaded program.  As of Python 1.5, the variables are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler.  The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses.  If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted.  If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost.  The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n',
  'types': u'\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python.  Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types.  Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.).\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\'  These are attributes that provide access to the\nimplementation and are not intended for general use.  Their definition\nmay change in the future.\n\nNone\n   This type has a single value.  There is a single object with this\n   value. This object is accessed through the built-in name ``None``.\n   It is used to signify the absence of a value in many situations,\n   e.g., it is returned from functions that don\'t explicitly return\n   anything. Its truth value is false.\n\nNotImplemented\n   This type has a single value.  There is a single object with this\n   value. This object is accessed through the built-in name\n   ``NotImplemented``. Numeric methods and rich comparison methods may\n   return this value if they do not implement the operation for the\n   operands provided.  (The interpreter will then try the reflected\n   operation, or some other fallback, depending on the operator.)  Its\n   truth value is true.\n\nEllipsis\n   This type has a single value.  There is a single object with this\n   value. This object is accessed through the built-in name\n   ``Ellipsis``. It is used to indicate the presence of the ``...``\n   syntax in a slice.  Its truth value is true.\n\n``numbers.Number``\n   These are created by numeric literals and returned as results by\n   arithmetic operators and arithmetic built-in functions.  Numeric\n   objects are immutable; once created their value never changes.\n   Python numbers are of course strongly related to mathematical\n   numbers, but subject to the limitations of numerical representation\n   in computers.\n\n   Python distinguishes between integers, floating point numbers, and\n   complex numbers:\n\n   ``numbers.Integral``\n      These represent elements from the mathematical set of integers\n      (positive and negative).\n\n      There are three types of integers:\n\n      Plain integers\n         These represent numbers in the range -2147483648 through\n         2147483647. (The range may be larger on machines with a\n         larger natural word size, but not smaller.)  When the result\n         of an operation would fall outside this range, the result is\n         normally returned as a long integer (in some cases, the\n         exception ``OverflowError`` is raised instead).  For the\n         purpose of shift and mask operations, integers are assumed to\n         have a binary, 2\'s complement notation using 32 or more bits,\n         and hiding no bits from the user (i.e., all 4294967296\n         different bit patterns correspond to different values).\n\n      Long integers\n         These represent numbers in an unlimited range, subject to\n         available (virtual) memory only.  For the purpose of shift\n         and mask operations, a binary representation is assumed, and\n         negative numbers are represented in a variant of 2\'s\n         complement which gives the illusion of an infinite string of\n         sign bits extending to the left.\n\n      Booleans\n         These represent the truth values False and True.  The two\n         objects representing the values False and True are the only\n         Boolean objects. The Boolean type is a subtype of plain\n         integers, and Boolean values behave like the values 0 and 1,\n         respectively, in almost all contexts, the exception being\n         that when converted to a string, the strings ``"False"`` or\n         ``"True"`` are returned, respectively.\n\n      The rules for integer representation are intended to give the\n      most meaningful interpretation of shift and mask operations\n      involving negative integers and the least surprises when\n      switching between the plain and long integer domains.  Any\n      operation, if it yields a result in the plain integer domain,\n      will yield the same result in the long integer domain or when\n      using mixed operands.  The switch between domains is transparent\n      to the programmer.\n\n   ``numbers.Real`` (``float``)\n      These represent machine-level double precision floating point\n      numbers. You are at the mercy of the underlying machine\n      architecture (and C or Java implementation) for the accepted\n      range and handling of overflow. Python does not support single-\n      precision floating point numbers; the savings in processor and\n      memory usage that are usually the reason for using these is\n      dwarfed by the overhead of using objects in Python, so there is\n      no reason to complicate the language with two kinds of floating\n      point numbers.\n\n   ``numbers.Complex``\n      These represent complex numbers as a pair of machine-level\n      double precision floating point numbers.  The same caveats apply\n      as for floating point numbers. The real and imaginary parts of a\n      complex number ``z`` can be retrieved through the read-only\n      attributes ``z.real`` and ``z.imag``.\n\nSequences\n   These represent finite ordered sets indexed by non-negative\n   numbers. The built-in function ``len()`` returns the number of\n   items of a sequence. When the length of a sequence is *n*, the\n   index set contains the numbers 0, 1, ..., *n*-1.  Item *i* of\n   sequence *a* is selected by ``a[i]``.\n\n   Sequences also support slicing: ``a[i:j]`` selects all items with\n   index *k* such that *i* ``<=`` *k* ``<`` *j*.  When used as an\n   expression, a slice is a sequence of the same type.  This implies\n   that the index set is renumbered so that it starts at 0.\n\n   Some sequences also support "extended slicing" with a third "step"\n   parameter: ``a[i:j:k]`` selects all items of *a* with index *x*\n   where ``x = i + n*k``, *n* ``>=`` ``0`` and *i* ``<=`` *x* ``<``\n   *j*.\n\n   Sequences are distinguished according to their mutability:\n\n   Immutable sequences\n      An object of an immutable sequence type cannot change once it is\n      created.  (If the object contains references to other objects,\n      these other objects may be mutable and may be changed; however,\n      the collection of objects directly referenced by an immutable\n      object cannot change.)\n\n      The following types are immutable sequences:\n\n      Strings\n         The items of a string are characters.  There is no separate\n         character type; a character is represented by a string of one\n         item. Characters represent (at least) 8-bit bytes.  The\n         built-in functions ``chr()`` and ``ord()`` convert between\n         characters and nonnegative integers representing the byte\n         values.  Bytes with the values 0-127 usually represent the\n         corresponding ASCII values, but the interpretation of values\n         is up to the program.  The string data type is also used to\n         represent arrays of bytes, e.g., to hold data read from a\n         file.\n\n         (On systems whose native character set is not ASCII, strings\n         may use EBCDIC in their internal representation, provided the\n         functions ``chr()`` and ``ord()`` implement a mapping between\n         ASCII and EBCDIC, and string comparison preserves the ASCII\n         order. Or perhaps someone can propose a better rule?)\n\n      Unicode\n         The items of a Unicode object are Unicode code units.  A\n         Unicode code unit is represented by a Unicode object of one\n         item and can hold either a 16-bit or 32-bit value\n         representing a Unicode ordinal (the maximum value for the\n         ordinal is given in ``sys.maxunicode``, and depends on how\n         Python is configured at compile time).  Surrogate pairs may\n         be present in the Unicode object, and will be reported as two\n         separate items.  The built-in functions ``unichr()`` and\n         ``ord()`` convert between code units and nonnegative integers\n         representing the Unicode ordinals as defined in the Unicode\n         Standard 3.0. Conversion from and to other encodings are\n         possible through the Unicode method ``encode()`` and the\n         built-in function ``unicode()``.\n\n      Tuples\n         The items of a tuple are arbitrary Python objects. Tuples of\n         two or more items are formed by comma-separated lists of\n         expressions.  A tuple of one item (a \'singleton\') can be\n         formed by affixing a comma to an expression (an expression by\n         itself does not create a tuple, since parentheses must be\n         usable for grouping of expressions).  An empty tuple can be\n         formed by an empty pair of parentheses.\n\n   Mutable sequences\n      Mutable sequences can be changed after they are created.  The\n      subscription and slicing notations can be used as the target of\n      assignment and ``del`` (delete) statements.\n\n      There is currently a single intrinsic mutable sequence type:\n\n      Lists\n         The items of a list are arbitrary Python objects.  Lists are\n         formed by placing a comma-separated list of expressions in\n         square brackets. (Note that there are no special cases needed\n         to form lists of length 0 or 1.)\n\n      The extension module ``array`` provides an additional example of\n      a mutable sequence type.\n\nSet types\n   These represent unordered, finite sets of unique, immutable\n   objects. As such, they cannot be indexed by any subscript. However,\n   they can be iterated over, and the built-in function ``len()``\n   returns the number of items in a set. Common uses for sets are fast\n   membership testing, removing duplicates from a sequence, and\n   computing mathematical operations such as intersection, union,\n   difference, and symmetric difference.\n\n   For set elements, the same immutability rules apply as for\n   dictionary keys. Note that numeric types obey the normal rules for\n   numeric comparison: if two numbers compare equal (e.g., ``1`` and\n   ``1.0``), only one of them can be contained in a set.\n\n   There are currently two intrinsic set types:\n\n   Sets\n      These represent a mutable set. They are created by the built-in\n      ``set()`` constructor and can be modified afterwards by several\n      methods, such as ``add()``.\n\n   Frozen sets\n      These represent an immutable set.  They are created by the\n      built-in ``frozenset()`` constructor.  As a frozenset is\n      immutable and *hashable*, it can be used again as an element of\n      another set, or as a dictionary key.\n\nMappings\n   These represent finite sets of objects indexed by arbitrary index\n   sets. The subscript notation ``a[k]`` selects the item indexed by\n   ``k`` from the mapping ``a``; this can be used in expressions and\n   as the target of assignments or ``del`` statements. The built-in\n   function ``len()`` returns the number of items in a mapping.\n\n   There is currently a single intrinsic mapping type:\n\n   Dictionaries\n      These represent finite sets of objects indexed by nearly\n      arbitrary values.  The only types of values not acceptable as\n      keys are values containing lists or dictionaries or other\n      mutable types that are compared by value rather than by object\n      identity, the reason being that the efficient implementation of\n      dictionaries requires a key\'s hash value to remain constant.\n      Numeric types used for keys obey the normal rules for numeric\n      comparison: if two numbers compare equal (e.g., ``1`` and\n      ``1.0``) then they can be used interchangeably to index the same\n      dictionary entry.\n\n      Dictionaries are mutable; they can be created by the ``{...}``\n      notation (see section *Dictionary displays*).\n\n      The extension modules ``dbm``, ``gdbm``, and ``bsddb`` provide\n      additional examples of mapping types.\n\nCallable types\n   These are the types to which the function call operation (see\n   section *Calls*) can be applied:\n\n   User-defined functions\n      A user-defined function object is created by a function\n      definition (see section *Function definitions*).  It should be\n      called with an argument list containing the same number of items\n      as the function\'s formal parameter list.\n\n      Special attributes:\n\n      +-------------------------+---------------------------------+-------------+\n      | Attribute               | Meaning                         |             |\n      +=========================+=================================+=============+\n      | ``func_doc``            | The function\'s documentation    | Writable    |\n      |                         | string, or ``None`` if          |             |\n      |                         | unavailable                     |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__doc__``             | Another way of spelling         | Writable    |\n      |                         | ``func_doc``                    |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``func_name``           | The function\'s name             | Writable    |\n      +-------------------------+---------------------------------+-------------+\n      | ``__name__``            | Another way of spelling         | Writable    |\n      |                         | ``func_name``                   |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__module__``          | The name of the module the      | Writable    |\n      |                         | function was defined in, or     |             |\n      |                         | ``None`` if unavailable.        |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``func_defaults``       | A tuple containing default      | Writable    |\n      |                         | argument values for those       |             |\n      |                         | arguments that have defaults,   |             |\n      |                         | or ``None`` if no arguments     |             |\n      |                         | have a default value            |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``func_code``           | The code object representing    | Writable    |\n      |                         | the compiled function body.     |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``func_globals``        | A reference to the dictionary   | Read-only   |\n      |                         | that holds the function\'s       |             |\n      |                         | global variables --- the global |             |\n      |                         | namespace of the module in      |             |\n      |                         | which the function was defined. |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``func_dict``           | The namespace supporting        | Writable    |\n      |                         | arbitrary function attributes.  |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``func_closure``        | ``None`` or a tuple of cells    | Read-only   |\n      |                         | that contain bindings for the   |             |\n      |                         | function\'s free variables.      |             |\n      +-------------------------+---------------------------------+-------------+\n\n      Most of the attributes labelled "Writable" check the type of the\n      assigned value.\n\n      Changed in version 2.4: ``func_name`` is now writable.\n\n      Function objects also support getting and setting arbitrary\n      attributes, which can be used, for example, to attach metadata\n      to functions.  Regular attribute dot-notation is used to get and\n      set such attributes. *Note that the current implementation only\n      supports function attributes on user-defined functions. Function\n      attributes on built-in functions may be supported in the\n      future.*\n\n      Additional information about a function\'s definition can be\n      retrieved from its code object; see the description of internal\n      types below.\n\n   User-defined methods\n      A user-defined method object combines a class, a class instance\n      (or ``None``) and any callable object (normally a user-defined\n      function).\n\n      Special read-only attributes: ``im_self`` is the class instance\n      object, ``im_func`` is the function object; ``im_class`` is the\n      class of ``im_self`` for bound methods or the class that asked\n      for the method for unbound methods; ``__doc__`` is the method\'s\n      documentation (same as ``im_func.__doc__``); ``__name__`` is the\n      method name (same as ``im_func.__name__``); ``__module__`` is\n      the name of the module the method was defined in, or ``None`` if\n      unavailable.\n\n      Changed in version 2.2: ``im_self`` used to refer to the class\n      that defined the method.\n\n      Changed in version 2.6: For 3.0 forward-compatibility,\n      ``im_func`` is also available as ``__func__``, and ``im_self``\n      as ``__self__``.\n\n      Methods also support accessing (but not setting) the arbitrary\n      function attributes on the underlying function object.\n\n      User-defined method objects may be created when getting an\n      attribute of a class (perhaps via an instance of that class), if\n      that attribute is a user-defined function object, an unbound\n      user-defined method object, or a class method object. When the\n      attribute is a user-defined method object, a new method object\n      is only created if the class from which it is being retrieved is\n      the same as, or a derived class of, the class stored in the\n      original method object; otherwise, the original method object is\n      used as it is.\n\n      When a user-defined method object is created by retrieving a\n      user-defined function object from a class, its ``im_self``\n      attribute is ``None`` and the method object is said to be\n      unbound. When one is created by retrieving a user-defined\n      function object from a class via one of its instances, its\n      ``im_self`` attribute is the instance, and the method object is\n      said to be bound. In either case, the new method\'s ``im_class``\n      attribute is the class from which the retrieval takes place, and\n      its ``im_func`` attribute is the original function object.\n\n      When a user-defined method object is created by retrieving\n      another method object from a class or instance, the behaviour is\n      the same as for a function object, except that the ``im_func``\n      attribute of the new instance is not the original method object\n      but its ``im_func`` attribute.\n\n      When a user-defined method object is created by retrieving a\n      class method object from a class or instance, its ``im_self``\n      attribute is the class itself (the same as the ``im_class``\n      attribute), and its ``im_func`` attribute is the function object\n      underlying the class method.\n\n      When an unbound user-defined method object is called, the\n      underlying function (``im_func``) is called, with the\n      restriction that the first argument must be an instance of the\n      proper class (``im_class``) or of a derived class thereof.\n\n      When a bound user-defined method object is called, the\n      underlying function (``im_func``) is called, inserting the class\n      instance (``im_self``) in front of the argument list.  For\n      instance, when ``C`` is a class which contains a definition for\n      a function ``f()``, and ``x`` is an instance of ``C``, calling\n      ``x.f(1)`` is equivalent to calling ``C.f(x, 1)``.\n\n      When a user-defined method object is derived from a class method\n      object, the "class instance" stored in ``im_self`` will actually\n      be the class itself, so that calling either ``x.f(1)`` or\n      ``C.f(1)`` is equivalent to calling ``f(C,1)`` where ``f`` is\n      the underlying function.\n\n      Note that the transformation from function object to (unbound or\n      bound) method object happens each time the attribute is\n      retrieved from the class or instance. In some cases, a fruitful\n      optimization is to assign the attribute to a local variable and\n      call that local variable. Also notice that this transformation\n      only happens for user-defined functions; other callable objects\n      (and all non-callable objects) are retrieved without\n      transformation.  It is also important to note that user-defined\n      functions which are attributes of a class instance are not\n      converted to bound methods; this *only* happens when the\n      function is an attribute of the class.\n\n   Generator functions\n      A function or method which uses the ``yield`` statement (see\n      section *The yield statement*) is called a *generator function*.\n      Such a function, when called, always returns an iterator object\n      which can be used to execute the body of the function:  calling\n      the iterator\'s ``next()`` method will cause the function to\n      execute until it provides a value using the ``yield`` statement.\n      When the function executes a ``return`` statement or falls off\n      the end, a ``StopIteration`` exception is raised and the\n      iterator will have reached the end of the set of values to be\n      returned.\n\n   Built-in functions\n      A built-in function object is a wrapper around a C function.\n      Examples of built-in functions are ``len()`` and ``math.sin()``\n      (``math`` is a standard built-in module). The number and type of\n      the arguments are determined by the C function. Special read-\n      only attributes: ``__doc__`` is the function\'s documentation\n      string, or ``None`` if unavailable; ``__name__`` is the\n      function\'s name; ``__self__`` is set to ``None`` (but see the\n      next item); ``__module__`` is the name of the module the\n      function was defined in or ``None`` if unavailable.\n\n   Built-in methods\n      This is really a different disguise of a built-in function, this\n      time containing an object passed to the C function as an\n      implicit extra argument.  An example of a built-in method is\n      ``alist.append()``, assuming *alist* is a list object. In this\n      case, the special read-only attribute ``__self__`` is set to the\n      object denoted by *list*.\n\n   Class Types\n      Class types, or "new-style classes," are callable.  These\n      objects normally act as factories for new instances of\n      themselves, but variations are possible for class types that\n      override ``__new__()``.  The arguments of the call are passed to\n      ``__new__()`` and, in the typical case, to ``__init__()`` to\n      initialize the new instance.\n\n   Classic Classes\n      Class objects are described below.  When a class object is\n      called, a new class instance (also described below) is created\n      and returned.  This implies a call to the class\'s ``__init__()``\n      method if it has one.  Any arguments are passed on to the\n      ``__init__()`` method.  If there is no ``__init__()`` method,\n      the class must be called without arguments.\n\n   Class instances\n      Class instances are described below.  Class instances are\n      callable only when the class has a ``__call__()`` method;\n      ``x(arguments)`` is a shorthand for ``x.__call__(arguments)``.\n\nModules\n   Modules are imported by the ``import`` statement (see section *The\n   import statement*). A module object has a namespace implemented by\n   a dictionary object (this is the dictionary referenced by the\n   func_globals attribute of functions defined in the module).\n   Attribute references are translated to lookups in this dictionary,\n   e.g., ``m.x`` is equivalent to ``m.__dict__["x"]``. A module object\n   does not contain the code object used to initialize the module\n   (since it isn\'t needed once the initialization is done).\n\n   Attribute assignment updates the module\'s namespace dictionary,\n   e.g., ``m.x = 1`` is equivalent to ``m.__dict__["x"] = 1``.\n\n   Special read-only attribute: ``__dict__`` is the module\'s namespace\n   as a dictionary object.\n\n   Predefined (writable) attributes: ``__name__`` is the module\'s\n   name; ``__doc__`` is the module\'s documentation string, or ``None``\n   if unavailable; ``__file__`` is the pathname of the file from which\n   the module was loaded, if it was loaded from a file. The\n   ``__file__`` attribute is not present for C modules that are\n   statically linked into the interpreter; for extension modules\n   loaded dynamically from a shared library, it is the pathname of the\n   shared library file.\n\nClasses\n   Both class types (new-style classes) and class objects (old-\n   style/classic classes) are typically created by class definitions\n   (see section *Class definitions*).  A class has a namespace\n   implemented by a dictionary object. Class attribute references are\n   translated to lookups in this dictionary, e.g., ``C.x`` is\n   translated to ``C.__dict__["x"]`` (although for new-style classes\n   in particular there are a number of hooks which allow for other\n   means of locating attributes). When the attribute name is not found\n   there, the attribute search continues in the base classes.  For\n   old-style classes, the search is depth-first, left-to-right in the\n   order of occurrence in the base class list. New-style classes use\n   the more complex C3 method resolution order which behaves correctly\n   even in the presence of \'diamond\' inheritance structures where\n   there are multiple inheritance paths leading back to a common\n   ancestor. Additional details on the C3 MRO used by new-style\n   classes can be found in the documentation accompanying the 2.3\n   release at http://www.python.org/download/releases/2.3/mro/.\n\n   When a class attribute reference (for class ``C``, say) would yield\n   a user-defined function object or an unbound user-defined method\n   object whose associated class is either ``C`` or one of its base\n   classes, it is transformed into an unbound user-defined method\n   object whose ``im_class`` attribute is ``C``. When it would yield a\n   class method object, it is transformed into a bound user-defined\n   method object whose ``im_class`` and ``im_self`` attributes are\n   both ``C``.  When it would yield a static method object, it is\n   transformed into the object wrapped by the static method object.\n   See section *Implementing Descriptors* for another way in which\n   attributes retrieved from a class may differ from those actually\n   contained in its ``__dict__`` (note that only new-style classes\n   support descriptors).\n\n   Class attribute assignments update the class\'s dictionary, never\n   the dictionary of a base class.\n\n   A class object can be called (see above) to yield a class instance\n   (see below).\n\n   Special attributes: ``__name__`` is the class name; ``__module__``\n   is the module name in which the class was defined; ``__dict__`` is\n   the dictionary containing the class\'s namespace; ``__bases__`` is a\n   tuple (possibly empty or a singleton) containing the base classes,\n   in the order of their occurrence in the base class list;\n   ``__doc__`` is the class\'s documentation string, or None if\n   undefined.\n\nClass instances\n   A class instance is created by calling a class object (see above).\n   A class instance has a namespace implemented as a dictionary which\n   is the first place in which attribute references are searched.\n   When an attribute is not found there, and the instance\'s class has\n   an attribute by that name, the search continues with the class\n   attributes.  If a class attribute is found that is a user-defined\n   function object or an unbound user-defined method object whose\n   associated class is the class (call it ``C``) of the instance for\n   which the attribute reference was initiated or one of its bases, it\n   is transformed into a bound user-defined method object whose\n   ``im_class`` attribute is ``C`` and whose ``im_self`` attribute is\n   the instance. Static method and class method objects are also\n   transformed, as if they had been retrieved from class ``C``; see\n   above under "Classes". See section *Implementing Descriptors* for\n   another way in which attributes of a class retrieved via its\n   instances may differ from the objects actually stored in the\n   class\'s ``__dict__``. If no class attribute is found, and the\n   object\'s class has a ``__getattr__()`` method, that is called to\n   satisfy the lookup.\n\n   Attribute assignments and deletions update the instance\'s\n   dictionary, never a class\'s dictionary.  If the class has a\n   ``__setattr__()`` or ``__delattr__()`` method, this is called\n   instead of updating the instance dictionary directly.\n\n   Class instances can pretend to be numbers, sequences, or mappings\n   if they have methods with certain special names.  See section\n   *Special method names*.\n\n   Special attributes: ``__dict__`` is the attribute dictionary;\n   ``__class__`` is the instance\'s class.\n\nFiles\n   A file object represents an open file.  File objects are created by\n   the ``open()`` built-in function, and also by ``os.popen()``,\n   ``os.fdopen()``, and the ``makefile()`` method of socket objects\n   (and perhaps by other functions or methods provided by extension\n   modules).  The objects ``sys.stdin``, ``sys.stdout`` and\n   ``sys.stderr`` are initialized to file objects corresponding to the\n   interpreter\'s standard input, output and error streams.  See *File\n   Objects* for complete documentation of file objects.\n\nInternal types\n   A few types used internally by the interpreter are exposed to the\n   user. Their definitions may change with future versions of the\n   interpreter, but they are mentioned here for completeness.\n\n   Code objects\n      Code objects represent *byte-compiled* executable Python code,\n      or *bytecode*. The difference between a code object and a\n      function object is that the function object contains an explicit\n      reference to the function\'s globals (the module in which it was\n      defined), while a code object contains no context; also the\n      default argument values are stored in the function object, not\n      in the code object (because they represent values calculated at\n      run-time).  Unlike function objects, code objects are immutable\n      and contain no references (directly or indirectly) to mutable\n      objects.\n\n      Special read-only attributes: ``co_name`` gives the function\n      name; ``co_argcount`` is the number of positional arguments\n      (including arguments with default values); ``co_nlocals`` is the\n      number of local variables used by the function (including\n      arguments); ``co_varnames`` is a tuple containing the names of\n      the local variables (starting with the argument names);\n      ``co_cellvars`` is a tuple containing the names of local\n      variables that are referenced by nested functions;\n      ``co_freevars`` is a tuple containing the names of free\n      variables; ``co_code`` is a string representing the sequence of\n      bytecode instructions; ``co_consts`` is a tuple containing the\n      literals used by the bytecode; ``co_names`` is a tuple\n      containing the names used by the bytecode; ``co_filename`` is\n      the filename from which the code was compiled;\n      ``co_firstlineno`` is the first line number of the function;\n      ``co_lnotab`` is a string encoding the mapping from bytecode\n      offsets to line numbers (for details see the source code of the\n      interpreter); ``co_stacksize`` is the required stack size\n      (including local variables); ``co_flags`` is an integer encoding\n      a number of flags for the interpreter.\n\n      The following flag bits are defined for ``co_flags``: bit\n      ``0x04`` is set if the function uses the ``*arguments`` syntax\n      to accept an arbitrary number of positional arguments; bit\n      ``0x08`` is set if the function uses the ``**keywords`` syntax\n      to accept arbitrary keyword arguments; bit ``0x20`` is set if\n      the function is a generator.\n\n      Future feature declarations (``from __future__ import\n      division``) also use bits in ``co_flags`` to indicate whether a\n      code object was compiled with a particular feature enabled: bit\n      ``0x2000`` is set if the function was compiled with future\n      division enabled; bits ``0x10`` and ``0x1000`` were used in\n      earlier versions of Python.\n\n      Other bits in ``co_flags`` are reserved for internal use.\n\n      If a code object represents a function, the first item in\n      ``co_consts`` is the documentation string of the function, or\n      ``None`` if undefined.\n\n   Frame objects\n      Frame objects represent execution frames.  They may occur in\n      traceback objects (see below).\n\n      Special read-only attributes: ``f_back`` is to the previous\n      stack frame (towards the caller), or ``None`` if this is the\n      bottom stack frame; ``f_code`` is the code object being executed\n      in this frame; ``f_locals`` is the dictionary used to look up\n      local variables; ``f_globals`` is used for global variables;\n      ``f_builtins`` is used for built-in (intrinsic) names;\n      ``f_restricted`` is a flag indicating whether the function is\n      executing in restricted execution mode; ``f_lasti`` gives the\n      precise instruction (this is an index into the bytecode string\n      of the code object).\n\n      Special writable attributes: ``f_trace``, if not ``None``, is a\n      function called at the start of each source code line (this is\n      used by the debugger); ``f_exc_type``, ``f_exc_value``,\n      ``f_exc_traceback`` represent the last exception raised in the\n      parent frame provided another exception was ever raised in the\n      current frame (in all other cases they are None); ``f_lineno``\n      is the current line number of the frame --- writing to this from\n      within a trace function jumps to the given line (only for the\n      bottom-most frame).  A debugger can implement a Jump command\n      (aka Set Next Statement) by writing to f_lineno.\n\n   Traceback objects\n      Traceback objects represent a stack trace of an exception.  A\n      traceback object is created when an exception occurs.  When the\n      search for an exception handler unwinds the execution stack, at\n      each unwound level a traceback object is inserted in front of\n      the current traceback.  When an exception handler is entered,\n      the stack trace is made available to the program. (See section\n      *The try statement*.) It is accessible as ``sys.exc_traceback``,\n      and also as the third item of the tuple returned by\n      ``sys.exc_info()``.  The latter is the preferred interface,\n      since it works correctly when the program is using multiple\n      threads. When the program contains no suitable handler, the\n      stack trace is written (nicely formatted) to the standard error\n      stream; if the interpreter is interactive, it is also made\n      available to the user as ``sys.last_traceback``.\n\n      Special read-only attributes: ``tb_next`` is the next level in\n      the stack trace (towards the frame where the exception\n      occurred), or ``None`` if there is no next level; ``tb_frame``\n      points to the execution frame of the current level;\n      ``tb_lineno`` gives the line number where the exception\n      occurred; ``tb_lasti`` indicates the precise instruction.  The\n      line number and last instruction in the traceback may differ\n      from the line number of its frame object if the exception\n      occurred in a ``try`` statement with no matching except clause\n      or with a finally clause.\n\n   Slice objects\n      Slice objects are used to represent slices when *extended slice\n      syntax* is used. This is a slice using two colons, or multiple\n      slices or ellipses separated by commas, e.g., ``a[i:j:step]``,\n      ``a[i:j, k:l]``, or ``a[..., i:j]``.  They are also created by\n      the built-in ``slice()`` function.\n\n      Special read-only attributes: ``start`` is the lower bound;\n      ``stop`` is the upper bound; ``step`` is the step value; each is\n      ``None`` if omitted. These attributes can have any type.\n\n      Slice objects support one method:\n\n      slice.indices(self, length)\n\n         This method takes a single integer argument *length* and\n         computes information about the extended slice that the slice\n         object would describe if applied to a sequence of *length*\n         items.  It returns a tuple of three integers; respectively\n         these are the *start* and *stop* indices and the *step* or\n         stride length of the slice. Missing or out-of-bounds indices\n         are handled in a manner consistent with regular slices.\n\n         New in version 2.3.\n\n   Static method objects\n      Static method objects provide a way of defeating the\n      transformation of function objects to method objects described\n      above. A static method object is a wrapper around any other\n      object, usually a user-defined method object. When a static\n      method object is retrieved from a class or a class instance, the\n      object actually returned is the wrapped object, which is not\n      subject to any further transformation. Static method objects are\n      not themselves callable, although the objects they wrap usually\n      are. Static method objects are created by the built-in\n      ``staticmethod()`` constructor.\n\n   Class method objects\n      A class method object, like a static method object, is a wrapper\n      around another object that alters the way in which that object\n      is retrieved from classes and class instances. The behaviour of\n      class method objects upon such retrieval is described above,\n      under "User-defined methods". Class method objects are created\n      by the built-in ``classmethod()`` constructor.\n',
  'typesfunctions': u'\nFunctions\n*********\n\nFunction objects are created by function definitions.  The only\noperation on a function object is to call it: ``func(argument-list)``.\n\nThere are really two flavors of function objects: built-in functions\nand user-defined functions.  Both support the same operation (to call\nthe function), but the implementation is different, hence the\ndifferent object types.\n\nSee *Function definitions* for more information.\n',
- 'typesmapping': u'\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects.  There is currently only one standard\nmapping type, the *dictionary*.  (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values.  Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys.  Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry.  (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass dict([arg])\n\n   Return a new dictionary initialized from an optional positional\n   argument or from a set of keyword arguments. If no arguments are\n   given, return a new empty dictionary. If the positional argument\n   *arg* is a mapping object, return a dictionary mapping the same\n   keys to the same values as does the mapping object. Otherwise the\n   positional argument must be a sequence, a container that supports\n   iteration, or an iterator object.  The elements of the argument\n   must each also be of one of those kinds, and each must in turn\n   contain exactly two objects. The first is used as a key in the new\n   dictionary, and the second as the key\'s value.  If a given key is\n   seen more than once, the last value associated with it is retained\n   in the new dictionary.\n\n   If keyword arguments are given, the keywords themselves with their\n   associated values are added as items to the dictionary. If a key is\n   specified both in the positional argument and as a keyword\n   argument, the value associated with the keyword is retained in the\n   dictionary. For example, these all return a dictionary equal to\n   ``{"one": 2, "two": 3}``:\n\n   * ``dict(one=2, two=3)``\n\n   * ``dict({\'one\': 2, \'two\': 3})``\n\n   * ``dict(zip((\'one\', \'two\'), (2, 3)))``\n\n   * ``dict([[\'two\', 3], [\'one\', 2]])``\n\n   The first example only works for keys that are valid Python\n   identifiers; the others work with any valid keys.\n\n   New in version 2.2.\n\n   Changed in version 2.3: Support for building a dictionary from\n   keyword arguments added.\n\n   These are the operations that dictionaries support (and therefore,\n   custom mapping types should support too):\n\n   len(d)\n\n      Return the number of items in the dictionary *d*.\n\n   d[key]\n\n      Return the item of *d* with key *key*.  Raises a ``KeyError`` if\n      *key* is not in the map.\n\n      New in version 2.5: If a subclass of dict defines a method\n      ``__missing__()``, if the key *key* is not present, the\n      ``d[key]`` operation calls that method with the key *key* as\n      argument.  The ``d[key]`` operation then returns or raises\n      whatever is returned or raised by the ``__missing__(key)`` call\n      if the key is not present. No other operations or methods invoke\n      ``__missing__()``. If ``__missing__()`` is not defined,\n      ``KeyError`` is raised.  ``__missing__()`` must be a method; it\n      cannot be an instance variable. For an example, see\n      ``collections.defaultdict``.\n\n   d[key] = value\n\n      Set ``d[key]`` to *value*.\n\n   del d[key]\n\n      Remove ``d[key]`` from *d*.  Raises a ``KeyError`` if *key* is\n      not in the map.\n\n   key in d\n\n      Return ``True`` if *d* has a key *key*, else ``False``.\n\n      New in version 2.2.\n\n   key not in d\n\n      Equivalent to ``not key in d``.\n\n      New in version 2.2.\n\n   clear()\n\n      Remove all items from the dictionary.\n\n   copy()\n\n      Return a shallow copy of the dictionary.\n\n   fromkeys(seq[, value])\n\n      Create a new dictionary with keys from *seq* and values set to\n      *value*.\n\n      ``fromkeys()`` is a class method that returns a new dictionary.\n      *value* defaults to ``None``.\n\n      New in version 2.3.\n\n   get(key[, default])\n\n      Return the value for *key* if *key* is in the dictionary, else\n      *default*. If *default* is not given, it defaults to ``None``,\n      so that this method never raises a ``KeyError``.\n\n   has_key(key)\n\n      ``dict.has_key(key)`` is equivalent to ``key in d``, but\n      deprecated.\n\n   items()\n\n      Return a copy of the dictionary\'s list of ``(key, value)``\n      pairs.\n\n      Note: Keys and values are listed in an arbitrary order which is non-\n        random, varies across Python implementations, and depends on\n        the dictionary\'s history of insertions and deletions. If\n        ``items()``, ``keys()``, ``values()``, ``iteritems()``,\n        ``iterkeys()``, and ``itervalues()`` are called with no\n        intervening modifications to the dictionary, the lists will\n        directly correspond.  This allows the creation of ``(value,\n        key)`` pairs using ``zip()``: ``pairs = zip(d.values(),\n        d.keys())``.  The same relationship holds for the\n        ``iterkeys()`` and ``itervalues()`` methods: ``pairs =\n        zip(d.itervalues(), d.iterkeys())`` provides the same value\n        for ``pairs``. Another way to create the same list is ``pairs\n        = [(v, k) for (k, v) in d.iteritems()]``.\n\n   iteritems()\n\n      Return an iterator over the dictionary\'s ``(key, value)`` pairs.\n      See the note for ``dict.items()``.\n\n      New in version 2.2.\n\n   iterkeys()\n\n      Return an iterator over the dictionary\'s keys.  See the note for\n      ``dict.items()``.\n\n      New in version 2.2.\n\n   itervalues()\n\n      Return an iterator over the dictionary\'s values.  See the note\n      for ``dict.items()``.\n\n      New in version 2.2.\n\n   keys()\n\n      Return a copy of the dictionary\'s list of keys.  See the note\n      for ``dict.items()``.\n\n   pop(key[, default])\n\n      If *key* is in the dictionary, remove it and return its value,\n      else return *default*.  If *default* is not given and *key* is\n      not in the dictionary, a ``KeyError`` is raised.\n\n      New in version 2.3.\n\n   popitem()\n\n      Remove and return an arbitrary ``(key, value)`` pair from the\n      dictionary.\n\n      ``popitem()`` is useful to destructively iterate over a\n      dictionary, as often used in set algorithms.  If the dictionary\n      is empty, calling ``popitem()`` raises a ``KeyError``.\n\n   setdefault(key[, default])\n\n      If *key* is in the dictionary, return its value.  If not, insert\n      *key* with a value of *default* and return *default*.  *default*\n      defaults to ``None``.\n\n   update([other])\n\n      Update the dictionary with the key/value pairs from *other*,\n      overwriting existing keys.  Return ``None``.\n\n      ``update()`` accepts either another dictionary object or an\n      iterable of key/value pairs (as a tuple or other iterable of\n      length two).  If keyword arguments are specified, the dictionary\n      is then is updated with those key/value pairs: ``d.update(red=1,\n      blue=2)``.\n\n      Changed in version 2.4: Allowed the argument to be an iterable\n      of key/value pairs and allowed keyword arguments.\n\n   values()\n\n      Return a copy of the dictionary\'s list of values.  See the note\n      for ``dict.items()``.\n',
+ 'typesmapping': u'\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects.  There is currently only one standard\nmapping type, the *dictionary*.  (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values.  Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys.  Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry.  (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass dict([arg])\n\n   Return a new dictionary initialized from an optional positional\n   argument or from a set of keyword arguments. If no arguments are\n   given, return a new empty dictionary. If the positional argument\n   *arg* is a mapping object, return a dictionary mapping the same\n   keys to the same values as does the mapping object. Otherwise the\n   positional argument must be a sequence, a container that supports\n   iteration, or an iterator object.  The elements of the argument\n   must each also be of one of those kinds, and each must in turn\n   contain exactly two objects. The first is used as a key in the new\n   dictionary, and the second as the key\'s value.  If a given key is\n   seen more than once, the last value associated with it is retained\n   in the new dictionary.\n\n   If keyword arguments are given, the keywords themselves with their\n   associated values are added as items to the dictionary. If a key is\n   specified both in the positional argument and as a keyword\n   argument, the value associated with the keyword is retained in the\n   dictionary. For example, these all return a dictionary equal to\n   ``{"one": 2, "two": 3}``:\n\n   * ``dict(one=2, two=3)``\n\n   * ``dict({\'one\': 2, \'two\': 3})``\n\n   * ``dict(zip((\'one\', \'two\'), (2, 3)))``\n\n   * ``dict([[\'two\', 3], [\'one\', 2]])``\n\n   The first example only works for keys that are valid Python\n   identifiers; the others work with any valid keys.\n\n   New in version 2.2.\n\n   Changed in version 2.3: Support for building a dictionary from\n   keyword arguments added.\n\n   These are the operations that dictionaries support (and therefore,\n   custom mapping types should support too):\n\n   len(d)\n\n      Return the number of items in the dictionary *d*.\n\n   d[key]\n\n      Return the item of *d* with key *key*.  Raises a ``KeyError`` if\n      *key* is not in the map.\n\n      New in version 2.5: If a subclass of dict defines a method\n      ``__missing__()``, if the key *key* is not present, the\n      ``d[key]`` operation calls that method with the key *key* as\n      argument.  The ``d[key]`` operation then returns or raises\n      whatever is returned or raised by the ``__missing__(key)`` call\n      if the key is not present. No other operations or methods invoke\n      ``__missing__()``. If ``__missing__()`` is not defined,\n      ``KeyError`` is raised.  ``__missing__()`` must be a method; it\n      cannot be an instance variable. For an example, see\n      ``collections.defaultdict``.\n\n   d[key] = value\n\n      Set ``d[key]`` to *value*.\n\n   del d[key]\n\n      Remove ``d[key]`` from *d*.  Raises a ``KeyError`` if *key* is\n      not in the map.\n\n   key in d\n\n      Return ``True`` if *d* has a key *key*, else ``False``.\n\n      New in version 2.2.\n\n   key not in d\n\n      Equivalent to ``not key in d``.\n\n      New in version 2.2.\n\n   clear()\n\n      Remove all items from the dictionary.\n\n   copy()\n\n      Return a shallow copy of the dictionary.\n\n   fromkeys(seq[, value])\n\n      Create a new dictionary with keys from *seq* and values set to\n      *value*.\n\n      ``fromkeys()`` is a class method that returns a new dictionary.\n      *value* defaults to ``None``.\n\n      New in version 2.3.\n\n   get(key[, default])\n\n      Return the value for *key* if *key* is in the dictionary, else\n      *default*. If *default* is not given, it defaults to ``None``,\n      so that this method never raises a ``KeyError``.\n\n   has_key(key)\n\n      Test for the presence of *key* in the dictionary.  ``has_key()``\n      is deprecated in favor of ``key in d``.\n\n   items()\n\n      Return a copy of the dictionary\'s list of ``(key, value)``\n      pairs.\n\n      Note: Keys and values are listed in an arbitrary order which is non-\n        random, varies across Python implementations, and depends on\n        the dictionary\'s history of insertions and deletions. If\n        ``items()``, ``keys()``, ``values()``, ``iteritems()``,\n        ``iterkeys()``, and ``itervalues()`` are called with no\n        intervening modifications to the dictionary, the lists will\n        directly correspond.  This allows the creation of ``(value,\n        key)`` pairs using ``zip()``: ``pairs = zip(d.values(),\n        d.keys())``.  The same relationship holds for the\n        ``iterkeys()`` and ``itervalues()`` methods: ``pairs =\n        zip(d.itervalues(), d.iterkeys())`` provides the same value\n        for ``pairs``. Another way to create the same list is ``pairs\n        = [(v, k) for (k, v) in d.iteritems()]``.\n\n   iteritems()\n\n      Return an iterator over the dictionary\'s ``(key, value)`` pairs.\n      See the note for ``dict.items()``.\n\n      New in version 2.2.\n\n   iterkeys()\n\n      Return an iterator over the dictionary\'s keys.  See the note for\n      ``dict.items()``.\n\n      New in version 2.2.\n\n   itervalues()\n\n      Return an iterator over the dictionary\'s values.  See the note\n      for ``dict.items()``.\n\n      New in version 2.2.\n\n   keys()\n\n      Return a copy of the dictionary\'s list of keys.  See the note\n      for ``dict.items()``.\n\n   pop(key[, default])\n\n      If *key* is in the dictionary, remove it and return its value,\n      else return *default*.  If *default* is not given and *key* is\n      not in the dictionary, a ``KeyError`` is raised.\n\n      New in version 2.3.\n\n   popitem()\n\n      Remove and return an arbitrary ``(key, value)`` pair from the\n      dictionary.\n\n      ``popitem()`` is useful to destructively iterate over a\n      dictionary, as often used in set algorithms.  If the dictionary\n      is empty, calling ``popitem()`` raises a ``KeyError``.\n\n   setdefault(key[, default])\n\n      If *key* is in the dictionary, return its value.  If not, insert\n      *key* with a value of *default* and return *default*.  *default*\n      defaults to ``None``.\n\n   update([other])\n\n      Update the dictionary with the key/value pairs from *other*,\n      overwriting existing keys.  Return ``None``.\n\n      ``update()`` accepts either another dictionary object or an\n      iterable of key/value pairs (as a tuple or other iterable of\n      length two).  If keyword arguments are specified, the dictionary\n      is then is updated with those key/value pairs: ``d.update(red=1,\n      blue=2)``.\n\n      Changed in version 2.4: Allowed the argument to be an iterable\n      of key/value pairs and allowed keyword arguments.\n\n   values()\n\n      Return a copy of the dictionary\'s list of values.  See the note\n      for ``dict.items()``.\n',
  'typesmethods': u"\nMethods\n*******\n\nMethods are functions that are called using the attribute notation.\nThere are two flavors: built-in methods (such as ``append()`` on\nlists) and class instance methods.  Built-in methods are described\nwith the types that support them.\n\nThe implementation adds two special read-only attributes to class\ninstance methods: ``m.im_self`` is the object on which the method\noperates, and ``m.im_func`` is the function implementing the method.\nCalling ``m(arg-1, arg-2, ..., arg-n)`` is completely equivalent to\ncalling ``m.im_func(m.im_self, arg-1, arg-2, ..., arg-n)``.\n\nClass instance methods are either *bound* or *unbound*, referring to\nwhether the method was accessed through an instance or a class,\nrespectively.  When a method is unbound, its ``im_self`` attribute\nwill be ``None`` and if called, an explicit ``self`` object must be\npassed as the first argument.  In this case, ``self`` must be an\ninstance of the unbound method's class (or a subclass of that class),\notherwise a ``TypeError`` is raised.\n\nLike function objects, methods objects support getting arbitrary\nattributes. However, since method attributes are actually stored on\nthe underlying function object (``meth.im_func``), setting method\nattributes on either bound or unbound methods is disallowed.\nAttempting to set a method attribute results in a ``TypeError`` being\nraised.  In order to set a method attribute, you need to explicitly\nset it on the underlying function object:\n\n   class C:\n       def method(self):\n           pass\n\n   c = C()\n   c.method.im_func.whoami = 'my name is c'\n\nSee *The standard type hierarchy* for more information.\n",
  'typesmodules': u"\nModules\n*******\n\nThe only special operation on a module is attribute access:\n``m.name``, where *m* is a module and *name* accesses a name defined\nin *m*'s symbol table. Module attributes can be assigned to.  (Note\nthat the ``import`` statement is not, strictly speaking, an operation\non a module object; ``import foo`` does not require a module object\nnamed *foo* to exist, rather it requires an (external) *definition*\nfor a module named *foo* somewhere.)\n\nA special member of every module is ``__dict__``. This is the\ndictionary containing the module's symbol table. Modifying this\ndictionary will actually change the module's symbol table, but direct\nassignment to the ``__dict__`` attribute is not possible (you can\nwrite ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but\nyou can't write ``m.__dict__ = {}``).  Modifying ``__dict__`` directly\nis not recommended.\n\nModules built into the interpreter are written like this: ``<module\n'sys' (built-in)>``.  If loaded from a file, they are written as\n``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.\n",
  'typesseq': u'\nSequence Types --- ``str``, ``unicode``, ``list``, ``tuple``, ``buffer``, ``xrange``\n************************************************************************************\n\nThere are six sequence types: strings, Unicode strings, lists, tuples,\nbuffers, and xrange objects. (For other containers see the built in\n``dict``, ``list``, ``set``, and ``tuple`` classes, and the\n``collections`` module.)\n\nString literals are written in single or double quotes: ``\'xyzzy\'``,\n``"frobozz"``.  See *String literals* for more about string literals.\nUnicode strings are much like strings, but are specified in the syntax\nusing a preceding ``\'u\'`` character: ``u\'abc\'``, ``u"def"``. In\naddition to the functionality described here, there are also string-\nspecific methods described in the *String Methods* section. Lists are\nconstructed with square brackets, separating items with commas: ``[a,\nb, c]``. Tuples are constructed by the comma operator (not within\nsquare brackets), with or without enclosing parentheses, but an empty\ntuple must have the enclosing parentheses, such as ``a, b, c`` or\n``()``.  A single item tuple must have a trailing comma, such as\n``(d,)``.\n\nBuffer objects are not directly supported by Python syntax, but can be\ncreated by calling the builtin function ``buffer()``.  They don\'t\nsupport concatenation or repetition.\n\nObjects of type xrange are similar to buffers in that there is no\nspecific syntax to create them, but they are created using the\n``xrange()`` function.  They don\'t support slicing, concatenation or\nrepetition, and using ``in``, ``not in``, ``min()`` or ``max()`` on\nthem is inefficient.\n\nMost sequence types support the following operations.  The ``in`` and\n``not in`` operations have the same priorities as the comparison\noperations.  The ``+`` and ``*`` operations have the same priority as\nthe corresponding numeric operations. [3] Additional methods are\nprovided for *Mutable Sequence Types*.\n\nThis table lists the sequence operations sorted in ascending priority\n(operations in the same box have the same priority).  In the table,\n*s* and *t* are sequences of the same type; *n*, *i* and *j* are\nintegers:\n\n+--------------------+----------------------------------+------------+\n| Operation          | Result                           | Notes      |\n+====================+==================================+============+\n| ``x in s``         | ``True`` if an item of *s* is    | (1)        |\n|                    | equal to *x*, else ``False``     |            |\n+--------------------+----------------------------------+------------+\n| ``x not in s``     | ``False`` if an item of *s* is   | (1)        |\n|                    | equal to *x*, else ``True``      |            |\n+--------------------+----------------------------------+------------+\n| ``s + t``          | the concatenation of *s* and *t* | (6)        |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s``   | *n* shallow copies of *s*        | (2)        |\n|                    | concatenated                     |            |\n+--------------------+----------------------------------+------------+\n| ``s[i]``           | *i*\'th item of *s*, origin 0     | (3)        |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]``         | slice of *s* from *i* to *j*     | (3)(4)     |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]``       | slice of *s* from *i* to *j*     | (3)(5)     |\n|                    | with step *k*                    |            |\n+--------------------+----------------------------------+------------+\n| ``len(s)``         | length of *s*                    |            |\n+--------------------+----------------------------------+------------+\n| ``min(s)``         | smallest item of *s*             |            |\n+--------------------+----------------------------------+------------+\n| ``max(s)``         | largest item of *s*              |            |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular, tuples and\nlists are compared lexicographically by comparing corresponding\nelements. This means that to compare equal, every element must compare\nequal and the two sequences must be of the same type and have the same\nlength. (For full details see *Comparisons* in the language\nreference.)\n\nNotes:\n\n1. When *s* is a string or Unicode string object the ``in`` and ``not\n   in`` operations act like a substring test.  In Python versions\n   before 2.3, *x* had to be a string of length 1. In Python 2.3 and\n   beyond, *x* may be a string of any length.\n\n2. Values of *n* less than ``0`` are treated as ``0`` (which yields an\n   empty sequence of the same type as *s*).  Note also that the copies\n   are shallow; nested structures are not copied.  This often haunts\n   new Python programmers; consider:\n\n   >>> lists = [[]] * 3\n   >>> lists\n   [[], [], []]\n   >>> lists[0].append(3)\n   >>> lists\n   [[3], [3], [3]]\n\n   What has happened is that ``[[]]`` is a one-element list containing\n   an empty list, so all three elements of ``[[]] * 3`` are (pointers\n   to) this single empty list.  Modifying any of the elements of\n   ``lists`` modifies this single list. You can create a list of\n   different lists this way:\n\n   >>> lists = [[] for i in range(3)]\n   >>> lists[0].append(3)\n   >>> lists[1].append(5)\n   >>> lists[2].append(7)\n   >>> lists\n   [[3], [5], [7]]\n\n3. If *i* or *j* is negative, the index is relative to the end of the\n   string: ``len(s) + i`` or ``len(s) + j`` is substituted.  But note\n   that ``-0`` is still ``0``.\n\n4. The slice of *s* from *i* to *j* is defined as the sequence of\n   items with index *k* such that ``i <= k < j``.  If *i* or *j* is\n   greater than ``len(s)``, use ``len(s)``.  If *i* is omitted or\n   ``None``, use ``0``.  If *j* is omitted or ``None``, use\n   ``len(s)``.  If *i* is greater than or equal to *j*, the slice is\n   empty.\n\n5. The slice of *s* from *i* to *j* with step *k* is defined as the\n   sequence of items with index  ``x = i + n*k`` such that ``0 <= n <\n   (j-i)/k``.  In other words, the indices are ``i``, ``i+k``,\n   ``i+2*k``, ``i+3*k`` and so on, stopping when *j* is reached (but\n   never including *j*).  If *i* or *j* is greater than ``len(s)``,\n   use ``len(s)``.  If *i* or *j* are omitted or ``None``, they become\n   "end" values (which end depends on the sign of *k*).  Note, *k*\n   cannot be zero. If *k* is ``None``, it is treated like ``1``.\n\n6. If *s* and *t* are both strings, some Python implementations such\n   as CPython can usually perform an in-place optimization for\n   assignments of the form ``s=s+t`` or ``s+=t``.  When applicable,\n   this optimization makes quadratic run-time much less likely.  This\n   optimization is both version and implementation dependent. For\n   performance sensitive code, it is preferable to use the\n   ``str.join()`` method which assures consistent linear concatenation\n   performance across versions and implementations.\n\n   Changed in version 2.4: Formerly, string concatenation never\n   occurred in-place.\n\n\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 only its first character\n   capitalized.\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 occurrences of substring *sub* in the range\n   [*start*, *end*].  Optional arguments *start* and *end* are\n   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 range [*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(format_string, *args, **kwargs)\n\n   Perform a string formatting operation.  The *format_string*\n   argument can contain literal text or replacement fields delimited\n   by braces ``{}``.  Each replacement field contains either the\n   numeric index of a positional argument, or the name of a keyword\n   argument.  Returns a copy of *format_string* where each replacement\n   field is replaced with the string value of the corresponding\n   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(seq)\n\n   Return a string which is the concatenation of the strings in the\n   sequence *seq*. The separator between elements is the string\n   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].  Optional\n   arguments *start* and *end* are interpreted as in slice notation.\n   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: words start with\n   uppercase characters, all remaining cased characters are lowercase.\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\n\nString Formatting Operations\n============================\n\nString and Unicode objects have one unique built-in operation: the\n``%`` operator (modulo).  This is also known as the string\n*formatting* or *interpolation* operator.  Given ``format % values``\n(where *format* is a string or Unicode object), ``%`` conversion\nspecifications in *format* are replaced with zero or more elements of\n*values*.  The effect is similar to the using ``sprintf`` in the C\nlanguage.  If *format* is a Unicode object, or if any of the objects\nbeing converted using the ``%s`` conversion are Unicode objects, the\nresult will also be a Unicode object.\n\nIf *format* requires a single argument, *values* may be a single non-\ntuple object. [4]  Otherwise, *values* must be a tuple with exactly\nthe number of items specified by the format string, or a single\nmapping object (for example, a dictionary).\n\nA conversion specifier contains two or more characters and has the\nfollowing components, which must occur in this order:\n\n1. The ``\'%\'`` character, which marks the start of the specifier.\n\n2. Mapping key (optional), consisting of a parenthesised sequence of\n   characters (for example, ``(somename)``).\n\n3. Conversion flags (optional), which affect the result of some\n   conversion types.\n\n4. Minimum field width (optional).  If specified as an ``\'*\'``\n   (asterisk), the actual width is read from the next element of the\n   tuple in *values*, and the object to convert comes after the\n   minimum field width and optional precision.\n\n5. Precision (optional), given as a ``\'.\'`` (dot) followed by the\n   precision.  If specified as ``\'*\'`` (an asterisk), the actual width\n   is read from the next element of the tuple in *values*, and the\n   value to convert comes after the precision.\n\n6. Length modifier (optional).\n\n7. Conversion type.\n\nWhen the right argument is a dictionary (or other mapping type), then\nthe formats in the string *must* include a parenthesised mapping key\ninto that dictionary inserted immediately after the ``\'%\'`` character.\nThe mapping key selects the value to be formatted from the mapping.\nFor example:\n\n>>> print \'%(language)s has %(#)03d quote types.\' % \\\n...       {\'language\': "Python", "#": 2}\nPython has 002 quote types.\n\nIn this case no ``*`` specifiers may occur in a format (since they\nrequire a sequential parameter list).\n\nThe conversion flag characters are:\n\n+-----------+-----------------------------------------------------------------------+\n| Flag      | Meaning                                                               |\n+===========+=======================================================================+\n| ``\'#\'``   | The value conversion will use the "alternate form" (where defined     |\n|           | below).                                                               |\n+-----------+-----------------------------------------------------------------------+\n| ``\'0\'``   | The conversion will be zero padded for numeric values.                |\n+-----------+-----------------------------------------------------------------------+\n| ``\'-\'``   | The converted value is left adjusted (overrides the ``\'0\'``           |\n|           | conversion if both are given).                                        |\n+-----------+-----------------------------------------------------------------------+\n| ``\' \'``   | (a space) A blank should be left before a positive number (or empty   |\n|           | string) produced by a signed conversion.                              |\n+-----------+-----------------------------------------------------------------------+\n| ``\'+\'``   | A sign character (``\'+\'`` or ``\'-\'``) will precede the conversion     |\n|           | (overrides a "space" flag).                                           |\n+-----------+-----------------------------------------------------------------------+\n\nA length modifier (``h``, ``l``, or ``L``) may be present, but is\nignored as it is not necessary for Python -- so e.g. ``%ld`` is\nidentical to ``%d``.\n\nThe conversion types are:\n\n+--------------+-------------------------------------------------------+---------+\n| Conversion   | Meaning                                               | Notes   |\n+==============+=======================================================+=========+\n| ``\'d\'``      | Signed integer decimal.                               |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'i\'``      | Signed integer decimal.                               |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'o\'``      | Signed octal value.                                   | (1)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'u\'``      | Obselete type -- it is identical to ``\'d\'``.          | (7)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'x\'``      | Signed hexadecimal (lowercase).                       | (2)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'X\'``      | Signed hexadecimal (uppercase).                       | (2)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'e\'``      | Floating point exponential format (lowercase).        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'E\'``      | Floating point exponential format (uppercase).        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'f\'``      | Floating point decimal format.                        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'F\'``      | Floating point decimal format.                        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'g\'``      | Floating point format. Uses lowercase exponential     | (4)     |\n|              | format if exponent is less than -4 or not less than   |         |\n|              | precision, decimal format otherwise.                  |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'G\'``      | Floating point format. Uses uppercase exponential     | (4)     |\n|              | format if exponent is less than -4 or not less than   |         |\n|              | precision, decimal format otherwise.                  |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'c\'``      | Single character (accepts integer or single character |         |\n|              | string).                                              |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'r\'``      | String (converts any python object using ``repr()``). | (5)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'s\'``      | String (converts any python object using ``str()``).  | (6)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'%\'``      | No argument is converted, results in a ``\'%\'``        |         |\n|              | character in the result.                              |         |\n+--------------+-------------------------------------------------------+---------+\n\nNotes:\n\n1. The alternate form causes a leading zero (``\'0\'``) to be inserted\n   between left-hand padding and the formatting of the number if the\n   leading character of the result is not already a zero.\n\n2. The alternate form causes a leading ``\'0x\'`` or ``\'0X\'`` (depending\n   on whether the ``\'x\'`` or ``\'X\'`` format was used) to be inserted\n   between left-hand padding and the formatting of the number if the\n   leading character of the result is not already a zero.\n\n3. The alternate form causes the result to always contain a decimal\n   point, even if no digits follow it.\n\n   The precision determines the number of digits after the decimal\n   point and defaults to 6.\n\n4. The alternate form causes the result to always contain a decimal\n   point, and trailing zeroes are not removed as they would otherwise\n   be.\n\n   The precision determines the number of significant digits before\n   and after the decimal point and defaults to 6.\n\n5. The ``%r`` conversion was added in Python 2.0.\n\n   The precision determines the maximal number of characters used.\n\n6. If the object or format provided is a ``unicode`` string, the\n   resulting string will also be ``unicode``.\n\n   The precision determines the maximal number of characters used.\n\n7. See **PEP 237**.\n\nSince Python strings have an explicit length, ``%s`` conversions do\nnot assume that ``\'\\0\'`` is the end of the string.\n\nFor safety reasons, floating point precisions are clipped to 50;\n``%f`` conversions for numbers whose absolute value is over 1e25 are\nreplaced by ``%g`` conversions. [5]  All other errors raise\nexceptions.\n\nAdditional string operations are defined in standard modules\n``string`` and ``re``.\n\n\nXRange Type\n===========\n\nThe ``xrange`` type is an immutable sequence which is commonly used\nfor looping.  The advantage of the ``xrange`` type is that an\n``xrange`` object will always take the same amount of memory, no\nmatter the size of the range it represents.  There are no consistent\nperformance advantages.\n\nXRange objects have very little behavior: they only support indexing,\niteration, and the ``len()`` function.\n\n\nMutable Sequence Types\n======================\n\nList objects support additional operations that allow in-place\nmodification of the object. Other mutable sequence types (when added\nto the language) should also support these operations. Strings and\ntuples are immutable sequence types: such objects cannot be modified\nonce created. The following operations are defined on mutable sequence\ntypes (where *x* is an arbitrary object):\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation                      | Result                           | Notes                 |\n+================================+==================================+=======================+\n| ``s[i] = x``                   | item *i* of *s* is replaced by   |                       |\n|                                | *x*                              |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t``                 | slice of *s* from *i* to *j* is  |                       |\n|                                | replaced by the contents of the  |                       |\n|                                | iterable *t*                     |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]``                 | same as ``s[i:j] = []``          |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t``               | the elements of ``s[i:j:k]`` are | (1)                   |\n|                                | replaced by those of *t*         |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]``               | removes the elements of          |                       |\n|                                | ``s[i:j:k]`` from the list       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)``                | same as ``s[len(s):len(s)] =     | (2)                   |\n|                                | [x]``                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (3)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)``                 | return number of *i*\'s for which |                       |\n|                                | ``s[i] == x``                    |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])``       | return smallest *k* such that    | (4)                   |\n|                                | ``s[k] == x`` and ``i <= k < j`` |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (5)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (6)                   |\n|                                | return x``                       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (4)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()``                | reverses the items of *s* in     | (7)                   |\n|                                | place                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([cmp[, key[,          | sort the items of *s* in place   | (7)(8)(9)(10)         |\n| reverse]]])``                  |                                  |                       |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is  replacing.\n\n2. The C implementation of Python has historically accepted multiple\n   parameters and implicitly joined them into a tuple; this no longer\n   works in Python 2.0.  Use of this misfeature has been deprecated\n   since Python 1.4.\n\n3. *x* can be any iterable object.\n\n4. Raises ``ValueError`` when *x* is not found in *s*. When a negative\n   index is passed as the second or third parameter to the ``index()``\n   method, the list length is added, as for slice indices.  If it is\n   still negative, it is truncated to zero, as for slice indices.\n\n   Changed in version 2.3: Previously, ``index()`` didn\'t have\n   arguments for specifying start and stop positions.\n\n5. When a negative index is passed as the first parameter to the\n   ``insert()`` method, the list length is added, as for slice\n   indices.  If it is still negative, it is truncated to zero, as for\n   slice indices.\n\n   Changed in version 2.3: Previously, all negative indices were\n   truncated to zero.\n\n6. The ``pop()`` method is only supported by the list and array types.\n   The optional argument *i* defaults to ``-1``, so that by default\n   the last item is removed and returned.\n\n7. The ``sort()`` and ``reverse()`` methods modify the list in place\n   for economy of space when sorting or reversing a large list.  To\n   remind you that they operate by side effect, they don\'t return the\n   sorted or reversed list.\n\n8. The ``sort()`` method takes optional arguments for controlling the\n   comparisons.\n\n   *cmp* specifies a custom comparison function of two arguments (list\n   items) which should return a negative, zero or positive number\n   depending on whether the first argument is considered smaller than,\n   equal to, or larger than the second argument: ``cmp=lambda x,y:\n   cmp(x.lower(), y.lower())``.  The default value is ``None``.\n\n   *key* specifies a function of one argument that is used to extract\n   a comparison key from each list element: ``key=str.lower``.  The\n   default value is ``None``.\n\n   *reverse* is a boolean value.  If set to ``True``, then the list\n   elements are sorted as if each comparison were reversed.\n\n   In general, the *key* and *reverse* conversion processes are much\n   faster than specifying an equivalent *cmp* function.  This is\n   because *cmp* is called multiple times for each list element while\n   *key* and *reverse* touch each element only once.\n\n   Changed in version 2.3: Support for ``None`` as an equivalent to\n   omitting *cmp* was added.\n\n   Changed in version 2.4: Support for *key* and *reverse* was added.\n\n9. Starting with Python 2.3, the ``sort()`` method is guaranteed to be\n   stable.  A sort is stable if it guarantees not to change the\n   relative order of elements that compare equal --- this is helpful\n   for sorting in multiple passes (for example, sort by department,\n   then by salary grade).\n\n10. While a list is being sorted, the effect of attempting to mutate,\n    or even inspect, the list is undefined.  The C implementation of\n    Python 2.3 and newer makes the list appear empty for the duration,\n    and raises ``ValueError`` if it can detect that the list has been\n    mutated during a sort.\n',
diff --git a/Misc/NEWS b/Misc/NEWS
index 300f7e7..abe8630 100644
--- a/Misc/NEWS
+++ b/Misc/NEWS
@@ -4,10 +4,10 @@ Python News
 
 (editors: check NEWS.help for information about editing NEWS using ReST.)
 
-What's New in Python 2.6.1 alpha 1
-==================================
+What's New in Python 2.6.1
+==========================
 
-*Release date: XX-XXX-2008*
+*Release date: 04-Dec-2008*
 
 Core and Builtins
 -----------------
diff --git a/Misc/RPM/python-2.6.spec b/Misc/RPM/python-2.6.spec
index f878fb2..d57c65d 100644
--- a/Misc/RPM/python-2.6.spec
+++ b/Misc/RPM/python-2.6.spec
@@ -34,7 +34,7 @@
 
 %define name python
 #--start constants--
-%define version 2.6
+%define version 2.6.1
 %define libver 2.6
 #--end constants--
 %define release 1pydotorg
diff --git a/README b/README
index 43f5485..0a5793e 100644
--- a/README
+++ b/README
@@ -1,5 +1,5 @@
-This is Python version 2.6
-==========================
+This is Python version 2.6.1
+============================
 
 Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008
 Python Software Foundation.