Barry Warsaw avatar Barry Warsaw committed a653214

Bumping to 3.0 final.

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Files changed (8)

Include/patchlevel.h

 #define PY_MAJOR_VERSION	3
 #define PY_MINOR_VERSION	0
 #define PY_MICRO_VERSION	0
-#define PY_RELEASE_LEVEL	PY_RELEASE_LEVEL_GAMMA
-#define PY_RELEASE_SERIAL	3
+#define PY_RELEASE_LEVEL	PY_RELEASE_LEVEL_FINAL
+#define PY_RELEASE_SERIAL	0
 
 /* Version as a string */
-#define PY_VERSION      	"3.0rc3+"
+#define PY_VERSION      	"3.0"
 /*--end constants--*/
 
 /* Subversion Revision number of this file (not of the repository) */

Lib/distutils/__init__.py

 #
 
 #--start constants--
-__version__ = "3.0rc3"
+__version__ = "3.0"
 #--end constants--

Lib/idlelib/idlever.py

-IDLE_VERSION = "3.0rc3"
+IDLE_VERSION = "3.0"

Lib/pydoc_topics.py

-# Autogenerated by Sphinx on Thu Nov 20 20:13:48 2008
+# Autogenerated by Sphinx on Wed Dec  3 12:00:16 2008
 topics = {'assert': '\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': '\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              | "*" target\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, optionally enclosed in\nparentheses or square brackets, is recursively defined as follows.\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:\n\n  * If the target list contains one target prefixed with an asterisk,\n    called a "starred" target: The object must be a sequence with at\n    least as many items as there are targets in the target list, minus\n    one.  The first items of the sequence are assigned, from left to\n    right, to the targets before the starred target.  The final items\n    of the sequence are assigned to the targets after the starred\n    target.  A list of the remaining items in the sequence is then\n    assigned to the starred target (the list can be empty).\n\n  * Else: The object must be a sequence with the same number of items\n    as there are targets in the target list, and the items are\n    assigned, from left to right, to the corresponding targets.\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`` or ``nonlocal``\n    statement in the current code block: the name is bound to the\n    object in the current local namespace.\n\n  * Otherwise: the name is bound to the object in the global namespace\n    or the outer namespace determined by ``nonlocal``, respectively.\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  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 an integer.  If it is negative, the sequence\'s\n  length is added to it.  The resulting value must be a nonnegative\n  integer less than the sequence\'s length, and the sequence is asked\n  to assign the assigned object to its item with that index.  If the\n  index is out of range, ``IndexError`` is raised (assignment to a\n  subscripted sequence cannot add new items to a 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  For user-defined objects, the ``__setitem__()`` method is called\n  with appropriate arguments.\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 integers. If either bound is\n  negative, the sequence\'s length is added to it.  The resulting\n  bounds are clipped to lie between zero and the sequence\'s length,\n  inclusive.  Finally, the sequence object is asked to replace the\n  slice with the items of the assigned sequence.  The length of the\n  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\nSee also:\n\n   **PEP 3132** - Extended Iterable Unpacking\n      The specification for the ``*target`` feature.\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': '\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',
  'callable-types': '\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',
  'calls': '\nCalls\n*****\n\nA call calls a callable object (e.g., a function) with a possibly\nempty series of arguments:\n\n   call                 ::= primary "(" [argument_list [","] | comprehension] ")"\n   argument_list        ::= positional_arguments ["," keyword_arguments]\n                       ["," "*" expression] ["," keyword_arguments]\n                       ["," "**" expression]\n                     | keyword_arguments ["," "*" expression]\n                       ["," keyword_arguments] ["," "**" expression]\n                     | "*" expression ["," keyword_arguments] ["," "**" expression]\n                     | "**" expression\n   positional_arguments ::= expression ("," expression)*\n   keyword_arguments    ::= keyword_item ("," keyword_item)*\n   keyword_item         ::= identifier "=" expression\n\nA trailing comma may be present after the positional and keyword\narguments but does not affect the semantics.\n\nThe primary must evaluate to a callable object (user-defined\nfunctions, built-in functions, methods of built-in objects, class\nobjects, methods of class instances, and all objects having a\n``__call__()`` method are callable).  All argument expressions are\nevaluated before the call is attempted.  Please refer to section\n*Function definitions* for the syntax of formal parameter lists.\n\nIf keyword arguments are present, they are first converted to\npositional arguments, as follows.  First, a list of unfilled slots is\ncreated for the formal parameters.  If there are N positional\narguments, they are placed in the first N slots.  Next, for each\nkeyword argument, the identifier is used to determine the\ncorresponding slot (if the identifier is the same as the first formal\nparameter name, the first slot is used, and so on).  If the slot is\nalready filled, a ``TypeError`` exception is raised. Otherwise, the\nvalue of the argument is placed in the slot, filling it (even if the\nexpression is ``None``, it fills the slot).  When all arguments have\nbeen processed, the slots that are still unfilled are filled with the\ncorresponding default value from the function definition.  (Default\nvalues are calculated, once, when the function is defined; thus, a\nmutable object such as a list or dictionary used as default value will\nbe shared by all calls that don\'t specify an argument value for the\ncorresponding slot; this should usually be avoided.)  If there are any\nunfilled slots for which no default value is specified, a\n``TypeError`` exception is raised.  Otherwise, the list of filled\nslots is used as the argument list for the call.\n\nNote: An implementation may provide builtin functions whose positional\n  parameters do not have names, even if they are \'named\' for the\n  purpose of documentation, and which therefore cannot be supplied by\n  keyword.  In CPython, this is the case for functions implemented in\n  C that use ``PyArg_ParseTuple`` to parse their arguments.\n\nIf there are more positional arguments than there are formal parameter\nslots, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``*identifier`` is present; in this case, that formal\nparameter receives a tuple containing the excess positional arguments\n(or an empty tuple if there were no excess positional arguments).\n\nIf any keyword argument does not correspond to a formal parameter\nname, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``**identifier`` is present; in this case, that\nformal parameter receives a dictionary containing the excess keyword\narguments (using the keywords as keys and the argument values as\ncorresponding values), or a (new) empty dictionary if there were no\nexcess keyword arguments.\n\nIf the syntax ``*expression`` appears in the function call,\n``expression`` must evaluate to a sequence.  Elements from this\nsequence are treated as if they were additional positional arguments;\nif there are positional arguments *x1*,..., *xN*, and ``expression``\nevaluates to a sequence *y1*, ..., *yM*, this is equivalent to a call\nwith M+N positional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.\n\nA consequence of this is that although the ``*expression`` syntax may\nappear *after* some keyword arguments, it is processed *before* the\nkeyword arguments (and the ``**expression`` argument, if any -- see\nbelow).  So:\n\n   >>> def f(a, b):\n   ...  print(a, b)\n   ...\n   >>> f(b=1, *(2,))\n   2 1\n   >>> f(a=1, *(2,))\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in ?\n   TypeError: f() got multiple values for keyword argument \'a\'\n   >>> f(1, *(2,))\n   1 2\n\nIt is unusual for both keyword arguments and the ``*expression``\nsyntax to be used in the same call, so in practice this confusion does\nnot arise.\n\nIf the syntax ``**expression`` appears in the function call,\n``expression`` must evaluate to a mapping, the contents of which are\ntreated as additional keyword arguments.  In the case of a keyword\nappearing in both ``expression`` and as an explicit keyword argument,\na ``TypeError`` exception is raised.\n\nFormal parameters using the syntax ``*identifier`` or ``**identifier``\ncannot be used as positional argument slots or as keyword argument\nnames.\n\nA call always returns some value, possibly ``None``, unless it raises\nan exception.  How this value is computed depends on the type of the\ncallable object.\n\nIf it is---\n\na user-defined function:\n   The code block for the function is executed, passing it the\n   argument list.  The first thing the code block will do is bind the\n   formal parameters to the arguments; this is described in section\n   *Function definitions*.  When the code block executes a ``return``\n   statement, this specifies the return value of the function call.\n\na built-in function or method:\n   The result is up to the interpreter; see *Built-in Functions* for\n   the descriptions of built-in functions and methods.\n\na class object:\n   A new instance of that class is returned.\n\na class instance method:\n   The corresponding user-defined function is called, with an argument\n   list that is one longer than the argument list of the call: the\n   instance becomes the first argument.\n\na class instance:\n   The class must define a ``__call__()`` method; the effect is then\n   the same as if that method was called.\n',
  'class': '\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n   classdef    ::= [decorators] "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\nClasses can also be decorated; as with functions,\n\n   @f1(arg)\n   @f2\n   class Foo: pass\n\nis equivalent to\n\n   class Foo: pass\n   Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``.  Both class and\ninstance 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.  Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n   **PEP 3129** - Class Decorators\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',
- 'comparisons': '\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 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,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes.  You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n  are identical to themselves, ``x is x`` but are not equal to\n  themselves, ``x != x``.  Additionally, comparing any value to a\n  not-a-number value will return ``False``.  For example, both ``3 <\n  float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n  values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  [3] String and bytes object can\'t be compared!\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. [4] Outcomes other than\n  equality are resolved consistently, but are not otherwise defined.\n  [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n  superset tests.  Those relations do not define total orderings (the\n  two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n  another, nor supersets of one another).  Accordingly, sets are not\n  appropriate arguments for functions which depend on total ordering.\n  For example, ``min()``, ``max()``, and ``sorted()`` produce\n  undefined results given a list of sets as inputs.\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\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison.  Most\nnumberic types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is.  When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``.  This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons.  For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership.  ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise.  ``x\nnot in s`` returns the negation of ``x in s``.  All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` equivalent to ``any(x is e or x == e for val e\nin y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\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. [6]\n',
+ 'comparisons': '\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 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,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes.  You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n  are identical to themselves, ``x is x`` but are not equal to\n  themselves, ``x != x``.  Additionally, comparing any value to a\n  not-a-number value will return ``False``.  For example, both ``3 <\n  float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n  values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  [3] String and bytes object can\'t be compared!\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. [4] Outcomes other than\n  equality are resolved consistently, but are not otherwise defined.\n  [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n  superset tests.  Those relations do not define total orderings (the\n  two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n  another, nor supersets of one another).  Accordingly, sets are not\n  appropriate arguments for functions which depend on total ordering.\n  For example, ``min()``, ``max()``, and ``sorted()`` produce\n  undefined results given a list of sets as inputs.\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\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison.  Most\nnumeric types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is.  When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``.  This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons.  For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership.  ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise.  ``x\nnot in s`` returns the negation of ``x in s``.  All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` is equivalent to ``any(x is e or x == e for val\ne in y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\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. [6]\n',
  'compound': '\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, while the ``with`` statement\nallows the execution of initialization and finalization code around a\nblock of code.  Function and class definitions are also syntactically\ncompound 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()`` calls 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   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 (see *Assignment statements*), and then the suite is\nexecuted.  When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand 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\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\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop.  Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; 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\n  internal counter is used to keep track of which item is used next,\n  and this is incremented on each iteration.  When this counter has\n  reached the length of the sequence the loop terminates.  This means\n  that if the suite deletes the current (or a previous) item from the\n  sequence, the next item will be skipped (since it gets the index of\n  the 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\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 or a tuple containing an item compatible with the\nexception.\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 after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed.  All except\nclauses must have an executable block.  When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause.  This is as if\n\n   except E as N:\n       foo\n\nwas translated to\n\n   except E as N:\n       try:\n           foo\n       finally:\n           N = None\n           del N\n\nThat means that you have to assign the exception to a different name\nif you want to be able to refer to it after the except clause.  The\nreason for this is that with the traceback attached to them,\nexceptions will form a reference cycle with the stack frame, keeping\nall locals in that frame alive until the next garbage collection\noccurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting\nof: ``exc_type``, the exception class; ``exc_value``, the exception\ninstance; ``exc_traceback``, a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. ``sys.exc_info()`` values 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\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\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   funcdef        ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n   decorators     ::= decorator+\n   decorator      ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n   dotted_name    ::= identifier ("." identifier)*\n   parameter_list ::= (defparameter ",")*\n                      (  "*" [parameter] ("," defparameter)*\n                      [, "**" parameter]\n                      | "**" parameter\n                      | defparameter [","] )\n   parameter      ::= identifier [":" expression]\n   defparameter   ::= parameter ["=" expression]\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 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 up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that 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. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name.  Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``.  Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list.  These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code.  The presence of annotations does not change the\nsemantics of a function.  The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\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 and annotations.\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    ::= [decorators] "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\nClasses can also be decorated; as with functions,\n\n   @f1(arg)\n   @f2\n   class Foo: pass\n\nis equivalent to\n\n   class Foo: pass\n   Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``.  Both class and\ninstance 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.  Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n   **PEP 3129** - Class Decorators\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': '\nWith Statement Context Managers\n*******************************\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': '\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',
  'if': '\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': '\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': '\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 3.0 are ``absolute_import``,\n``division``, ``generators``, ``unicode_literals``,\n``print_function``, ``nested_scopes`` and ``with_statement``.  They\nare all redundant because they are always enabled, and only kept for\nbackwards compatibility.\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 calls to the builtin functions ``exec()`` and\n``compile()`` that occur in a module ``M`` containing a future\nstatement will, by default, use the new syntax or semantics associated\nwith the future statement.  This can be controlled by optional\narguments to ``compile()`` --- see the documentation of that function\nfor 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': '\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 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,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes.  You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n  are identical to themselves, ``x is x`` but are not equal to\n  themselves, ``x != x``.  Additionally, comparing any value to a\n  not-a-number value will return ``False``.  For example, both ``3 <\n  float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n  values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  [3] String and bytes object can\'t be compared!\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. [4] Outcomes other than\n  equality are resolved consistently, but are not otherwise defined.\n  [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n  superset tests.  Those relations do not define total orderings (the\n  two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n  another, nor supersets of one another).  Accordingly, sets are not\n  appropriate arguments for functions which depend on total ordering.\n  For example, ``min()``, ``max()``, and ``sorted()`` produce\n  undefined results given a list of sets as inputs.\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\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison.  Most\nnumberic types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is.  When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``.  This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons.  For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership.  ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise.  ``x\nnot in s`` returns the negation of ``x in s``.  All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` equivalent to ``any(x is e or x == e for val e\nin y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\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. [6]\n',
+ 'in': '\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 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,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes.  You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n  are identical to themselves, ``x is x`` but are not equal to\n  themselves, ``x != x``.  Additionally, comparing any value to a\n  not-a-number value will return ``False``.  For example, both ``3 <\n  float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n  values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  [3] String and bytes object can\'t be compared!\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. [4] Outcomes other than\n  equality are resolved consistently, but are not otherwise defined.\n  [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n  superset tests.  Those relations do not define total orderings (the\n  two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n  another, nor supersets of one another).  Accordingly, sets are not\n  appropriate arguments for functions which depend on total ordering.\n  For example, ``min()``, ``max()``, and ``sorted()`` produce\n  undefined results given a list of sets as inputs.\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\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison.  Most\nnumeric types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is.  When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``.  This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons.  For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership.  ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise.  ``x\nnot in s`` returns the negation of ``x in s``.  All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` is equivalent to ``any(x is e or x == e for val\ne in y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\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. [6]\n',
  'integers': '\nInteger literals\n****************\n\nInteger literals are described by the following lexical definitions:\n\n   integer        ::= decimalinteger | octinteger | hexinteger | bininteger\n   decimalinteger ::= nonzerodigit digit* | "0"+\n   nonzerodigit   ::= "1"..."9"\n   digit          ::= "0"..."9"\n   octinteger     ::= "0" ("o" | "O") octdigit+\n   hexinteger     ::= "0" ("x" | "X") hexdigit+\n   bininteger     ::= "0" ("b" | "B") bindigit+\n   octdigit       ::= "0"..."7"\n   hexdigit       ::= digit | "a"..."f" | "A"..."F"\n   bindigit       ::= "0" | "1"\n\nThere is no limit for the length of integer literals apart from what\ncan be stored in available memory.\n\nNote that leading zeros in a non-zero decimal number are not allowed.\nThis is for disambiguation with C-style octal literals, which Python\nused before version 3.0.\n\nSome examples of integer literals:\n\n   7     2147483647                        0o177    0b100110111\n   3     79228162514264337593543950336     0o377    0x100000000\n         79228162514264337593543950336              0xdeadbeef\n',
  'lambda': '\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': '\nList displays\n*************\n\nA list display is a possibly empty series of expressions enclosed in\nsquare brackets:\n\n   list_display ::= "[" [expression_list | comprehension] "]"\n\nA list display yields a new list object, the contents being specified\nby either a list of expressions or a comprehension.  When a comma-\nseparated list of expressions is supplied, its elements are evaluated\nfrom left to right and placed into the list object in that order.\nWhen a comprehension is supplied, the list is constructed from the\nelements resulting from the comprehension.\n',
 What's New in Python 3.0 final
 ==============================
 
-*Release date: XX-XXX-2008*
+*Release date: 03-Dec-2008*
 
 Core and Builtins
 -----------------
 Build
 -----
 
-- Issue #4407: Fix source file that caused the compileall step in Windows installer
-  to fail.
+- Issue #4407: Fix source file that caused the compileall step in Windows
+  installer to fail.
 
 Docs
 ----

Misc/RPM/python-3.0.spec

 
 %define name python
 #--start constants--
-%define version 3.0rc3
+%define version 3.0
 %define libver 3.0
 #--end constants--
 %define release 1pydotorg
-This is Python version 3.0 release candidate 3
-==============================================
+This is Python version 3.0 final
+================================
 
 For notes specific to this release, see RELNOTES in this directory.
 Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008
 Python Software Foundation.
 All rights reserved.
 
-Python 3000 (a.k.a. "Py3k", and released as Python 3.0) is a new
-version of the language, which is incompatible with the 2.x line of
-releases.  The language is mostly the same, but many details,
-especially how built-in objects like dictionaries and strings work,
-have changed considerably, and a lot of deprecated features have
-finally been removed.
-
-This is an ongoing project; the cleanup isn't expected to be complete
-until some time in 2008.  In particular there are plans to reorganize
-the standard library namespace.
-
-
-Release Schedule
-----------------
-
-The release plan is to have a series of alpha releases in 2007 and 2008,
-beta releases in 2008, and a final release in October 2008.  The alpha
-releases are primarily aimed at developers who want a sneak peek at the
-new langauge, especially those folks who plan to port their code to
-Python 3000.  The hope is that by the time of the final release, many
-3rd party packages will already be available in a 3.0-compatible form.
-
-See PEP 361 for release details: http://www.python.org/dev/peps/pep-0361/
+Python 3 (a.k.a. "Python 3000" or "Py3k", and released as Python 3.0) is a new
+version of the language, which is incompatible with the 2.x line of releases.
+The language is mostly the same, but many details, especially how built-in
+objects like dictionaries and strings work, have changed considerably, and a
+lot of deprecated features have finally been removed.
 
 
 Documentation
 -------------
 
-Documentation for Python 3000 is online, updated twice a day:
+Documentation for Python 3.0 is online, updated twice a day:
 
     http://docs.python.org/dev/3.0/
 
 All documentation is also available online at the Python web site
-(http://docs.python.org/, see below).  It is available online for
-occasional reference, or can be downloaded in many formats for faster
-access.  The documentation is downloadable in HTML, PostScript, PDF,
-LaTeX (through 2.5), and reStructuredText (2.6+) formats; the LaTeX and
-reStructuredText versions are primarily for documentation authors,
+(http://docs.python.org/, see below).  It is available online for occasional
+reference, and it can be downloaded in many formats for faster local access.
+The documentation is downloadable in HTML, PostScript, PDF, LaTeX (through
+2.5), and reStructuredText (2.6, 3.0, and going forward) formats; the LaTeX
+and reStructuredText versions are primarily for documentation authors,
 translators, and people with special formatting requirements.
 
 This is a work in progress; please help improve it!
 
-The design documents for Python 3000 are also online.  While the
-reference documentation is being updated, the PEPs are often the best
-source of information about new features.  Start by reading PEP 3000:
+The design documents for Python 3 are also online.  While the reference
+documentation is being updated, the PEPs are often the best source of
+information about new features.  Start by reading PEP 3000:
 
     http://python.org/dev/peps/pep-3000/
 
 What's New
 ----------
 
-For an overview of what's new in Python 3000, see Guido van Rossum's
-blog at artima.com:
+For an overview of what's new in Python 3.0, see Guido van Rossum's blog at
+artima.com:
 
     http://www.artima.com/weblogs/index.jsp?blogger=guido
 
-We try to eventually have a comprehensive overview of the changes in
-the "What's New in Python 3.0" document, found at
+We try to eventually have a comprehensive overview of the changes in the
+"What's New in Python 3.0" document, found at
 
     http://docs.python.org/dev/3.0/whatsnew/3.0
 
-Please help write it!
+Please help improve it!
 
-For a more detailed change log, read Misc/NEWS (though this file, too,
-is incomplete, and also doesn't list anything merged in from the 2.6
-release under development).
+For a more detailed change log, read Misc/NEWS, though this file, too, is
+incomplete, and also doesn't list anything merged in from the 2.6 release.
 
 If you want to install multiple versions of Python see the section below
 entitled "Installing multiple versions".
 -------------------------
 
 If you have a proposal to change Python, you may want to send an email to the
-comp.lang.python or python-ideas mailing lists for inital feedback. A Python
-Enhancement Proposal (PEP) may be submitted if your idea gains ground. All
+comp.lang.python or python-ideas mailing lists for initial feedback.  A Python
+Enhancement Proposal (PEP) may be submitted if your idea gains ground.  All
 current PEPs, as well as guidelines for submitting a new PEP, are listed at
 http://www.python.org/dev/peps/.
 
 Converting From Python 2.x to 3.0
 ---------------------------------
 
-Python 2.6 (to be released concurrent with Python 3.0) will contain features
-to help locating code that needs to be changed, such as optional warnings when
-deprecated features are used, and backported versions of certain key Python
-3000 features.
-
-
-Installing multiple versions
-----------------------------
-
-On Unix and Mac systems if you intend to install multiple versions of Python
-using the same installation prefix (--prefix argument to the configure
-script) you must take care that your primary python executable is not
-overwritten by the installation of a different versio.  All files and
-directories installed using "make altinstall" contain the major and minor
-version and can thus live side-by-side.  "make install" also creates
-${prefix}/bin/python which refers to ${prefix}/bin/pythonX.Y.  If you intend
-to install multiple versions using the same prefix you must decide which
-version (if any) is your "primary" version.  Install that version using
-"make install".  Install all other versions using "make altinstall".
-
-For example, if you want to install Python 2.5, 2.6 and 3.0 with 2.6 being
-the primary version, you would execute "make install" in your 2.6 build
-directory and "make altinstall" in the others.
-
-
-Configuration options and variables
------------------------------------
+Python 2.6 contains features to help locating and updating code that needs to
+be changed when migrating to Python 3.
 
 A source-to-source translation tool, "2to3", can take care of the
 mundane task of converting large amounts of source code.  It is not a
     http://svn.python.org/view/sandbox/trunk/2to3/
 
 
+Installing multiple versions
+----------------------------
+
+On Unix and Mac systems if you intend to install multiple versions of Python
+using the same installation prefix (--prefix argument to the configure script)
+you must take care that your primary python executable is not overwritten by
+the installation of a different version.  All files and directories installed
+using "make altinstall" contain the major and minor version and can thus live
+side-by-side.  "make install" also creates ${prefix}/bin/python which refers
+to ${prefix}/bin/pythonX.Y.  If you intend to install multiple versions using
+the same prefix you must decide which version (if any) is your "primary"
+version.  Install that version using "make install".  Install all other
+versions using "make altinstall".
+
+For example, if you want to install Python 2.5, 2.6 and 3.0 with 2.6 being the
+primary version, you would execute "make install" in your 2.6 build directory
+and "make altinstall" in the others.
+
+
 Issue Tracker and Mailing List
 ------------------------------
 
-We're soliciting bug reports about all aspects of the language.  Fixes
-are also welcome, preferable in unified diff format.  Please use the
-issue tracker:
+We're soliciting bug reports about all aspects of the language.  Fixes are
+also welcome, preferable in unified diff format.  Please use the issue
+tracker:
 
     http://bugs.python.org/
 
-If you're not sure whether you're dealing with a bug or a feature, use
-the mailing list:
+If you're not sure whether you're dealing with a bug or a feature, use the
+mailing list:
 
     python-3000@python.org
 
-To subscribe to the list, use the mailman form:
+To subscribe to the list, use the Mailman form:
 
     http://mail.python.org/mailman/listinfo/python-3000/
 
 
 * The email package needs quite a bit of work to make it consistent with
   respect to bytes and strings.  There have been discussions on
-  email-sig@python.org about where to go with the email package for 3.0, but
-  this was not resolved in time for 3.0 final.  With enough care though, the
-  email package in Python 3.0 should be about as usable as it is with Python
-  2.
+  email-sig@python.org about where to go with the email package for Python
+  3.0, but this was not resolved in time for 3.0 final.  With enough care
+  though, the email package in Python 3.0 should be about as usable as it is
+  with Python 2.
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