update pydoc-topics

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diff --git a/Lib/pydoc_data/topics.py b/Lib/pydoc_data/topics.py
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--- a/Lib/pydoc_data/topics.py
+++ b/Lib/pydoc_data/topics.py
@@ -1,4 +1,4 @@
-# Autogenerated by Sphinx on Sat May 17 17:29:52 2014
+# Autogenerated by Sphinx on Sun Jun 29 18:55:25 2014
 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\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable.  The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list is recursively defined as\nfollows.\n\n* If the target list is a single target: The object is assigned to\n  that target.\n\n* If the target list is a comma-separated list of targets: The object\n  must be an iterable with the same number of items as there are\n  targets in the target list, and the items are assigned, from left to\n  right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n  * If the name does not occur in a ``global`` statement in the\n    current code block: the name is bound to the object in the current\n    local namespace.\n\n  * Otherwise: the name is bound to the object in the current global\n    namespace.\n\n  The name is rebound if it was already bound.  This may cause the\n  reference count for the object previously bound to the name to reach\n  zero, causing the object to be deallocated and its destructor (if it\n  has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in square\n  brackets: The object must be an iterable with the same number of\n  items as there are targets in the target list, and its items are\n  assigned, from left to right, to the corresponding targets.\n\n* If the target is an attribute reference: The primary expression in\n  the reference is evaluated.  It should yield an object with\n  assignable attributes; if this is not the case, ``TypeError`` is\n  raised.  That object is then asked to assign the assigned object to\n  the given attribute; if it cannot perform the assignment, it raises\n  an exception (usually but not necessarily ``AttributeError``).\n\n  Note: If the object is a class instance and the attribute reference\n  occurs on both sides of the assignment operator, the RHS expression,\n  ``a.x`` can access either an instance attribute or (if no instance\n  attribute exists) a class attribute.  The LHS target ``a.x`` is\n  always set as an instance attribute, creating it if necessary.\n  Thus, the two occurrences of ``a.x`` do not necessarily refer to the\n  same attribute: if the RHS expression refers to a class attribute,\n  the LHS creates a new instance attribute as the target of the\n  assignment:\n\n     class Cls:\n         x = 3             # class variable\n     inst = Cls()\n     inst.x = inst.x + 1   # writes inst.x as 4 leaving Cls.x as 3\n\n  This description does not necessarily apply to descriptor\n  attributes, such as properties created with ``property()``.\n\n* If the target is a subscription: The primary expression in the\n  reference is evaluated.  It should yield either a mutable sequence\n  object (such as a list) or a mapping object (such as a dictionary).\n  Next, the subscript expression is evaluated.\n\n  If the primary is a mutable sequence object (such as a list), the\n  subscript must yield a plain integer.  If it is negative, the\n  sequence\'s length is added to it. The resulting value must be a\n  nonnegative integer less than the sequence\'s length, and the\n  sequence is asked to assign the assigned object to its item with\n  that index.  If the index is out of range, ``IndexError`` is raised\n  (assignment to a subscripted sequence cannot add new items to a\n  list).\n\n  If the primary is a mapping object (such as a dictionary), the\n  subscript must have a type compatible with the mapping\'s key type,\n  and the mapping is then asked to create a key/datum pair which maps\n  the subscript to the assigned object.  This can either replace an\n  existing key/value pair with the same key value, or insert a new\n  key/value pair (if no key with the same value existed).\n\n* If the target is a slicing: The primary expression in the reference\n  is evaluated.  It should yield a mutable sequence object (such as a\n  list).  The assigned object should be a sequence object of the same\n  type.  Next, the lower and upper bound expressions are evaluated,\n  insofar they are present; defaults are zero and the sequence\'s\n  length.  The bounds should evaluate to (small) integers.  If either\n  bound is negative, the sequence\'s length is added to it. The\n  resulting bounds are clipped to lie between zero and the sequence\'s\n  length, inclusive.  Finally, the sequence object is asked to replace\n  the slice with the items of the assigned sequence.  The length of\n  the slice may be different from the length of the assigned sequence,\n  thus changing the length of the target sequence, if the object\n  allows it.\n\n**CPython implementation detail:** In the current implementation, the\nsyntax for targets is taken to be the same as for expressions, and\ninvalid syntax is rejected during the code generation phase, causing\nless detailed error messages.\n\nWARNING: Although the definition of assignment implies that overlaps\nbetween the left-hand side and the right-hand side are \'safe\' (for\nexample ``a, b = b, a`` swaps two variables), overlaps *within* the\ncollection of assigned-to variables are not safe!  For instance, the\nfollowing program prints ``[0, 2]``:\n\n   x = [0, 1]\n   i = 0\n   i, x[i] = 1, 2\n   print x\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n   augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n   augtarget                 ::= identifier | attributeref | subscription | slicing\n   augop                     ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n             | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like ``x += 1`` can be rewritten as\n``x = x + 1`` to achieve a similar, but not exactly equal effect. In\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',
  'atom-identifiers': '\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, with leading underscores removed and a single underscore\ninserted, in front of the name.  For example, the identifier\n``__spam`` occurring in a class named ``Ham`` will be transformed to\n``_Ham__spam``.  This transformation is independent of the syntactical\ncontext in which the identifier is used.  If the transformed name is\nextremely long (longer than 255 characters), implementation defined\ntruncation may happen. If the class name consists only of underscores,\nno transformation is done.\n',
@@ -68,7 +68,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss
  'try': '\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n   try_stmt  ::= try1_stmt | try2_stmt\n   try1_stmt ::= "try" ":" suite\n                 ("except" [expression [("as" | ",") target]] ":" suite)+\n                 ["else" ":" suite]\n                 ["finally" ":" suite]\n   try2_stmt ::= "try" ":" suite\n                 "finally" ":" suite\n\nChanged in version 2.5: In previous versions of Python,\n``try``...``except``...``finally`` did not work. ``try``...``except``\nhad to be nested in ``try``...``finally``.\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started.  This search inspects the except\nclauses in turn until one is found that matches the exception.  An\nexpression-less except clause, if present, must be last; it matches\nany exception.  For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception.  An object is\ncompatible with an exception if it is the class or a base class of the\nexception object, 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 in that except clause, if present, and the except\nclause\'s suite is executed.  All except clauses must have an\nexecutable block.  When the end of this block is reached, execution\ncontinues normally after the entire try statement.  (This means that\nif two nested handlers exist for the same exception, and the exception\noccurs in the try clause of the inner handler, the outer handler will\nnot handle the exception.)\n\nBefore an except clause\'s suite is executed, details about the\nexception are assigned to three variables in the ``sys`` module:\n``sys.exc_type`` receives the object identifying the exception;\n``sys.exc_value`` receives the exception\'s parameter;\n``sys.exc_traceback`` receives a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. These details are also available through the\n``sys.exc_info()`` function, which returns a tuple ``(exc_type,\nexc_value, exc_traceback)``.  Use of the corresponding variables is\ndeprecated in favor of this function, since their use is unsafe in a\nthreaded program.  As of Python 1.5, the variables are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler.  The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses.  If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted.  If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is discarded:\n\n   >>> def f():\n   ...     try:\n   ...         1/0\n   ...     finally:\n   ...         return 42\n   ...\n   >>> f()\n   42\n\nThe exception information is not available to the program during\nexecution 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\nThe return value of a function is determined by the last ``return``\nstatement executed.  Since the ``finally`` clause always executes, a\n``return`` statement executed in the ``finally`` clause will always be\nthe last one executed:\n\n   >>> def foo():\n   ...     try:\n   ...         return \'try\'\n   ...     finally:\n   ...         return \'finally\'\n   ...\n   >>> foo()\n   \'finally\'\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n',
  'types': '\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python.  Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types.  Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.).\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\'  These are attributes that provide access to the\nimplementation and are not intended for general use.  Their definition\nmay change in the future.\n\nNone\n   This type has a single value.  There is a single object with this\n   value. This object is accessed through the built-in name ``None``.\n   It is used to signify the absence of a value in many situations,\n   e.g., it is returned from functions that don\'t explicitly return\n   anything. Its truth value is false.\n\nNotImplemented\n   This type has a single value.  There is a single object with this\n   value. This object is accessed through the built-in name\n   ``NotImplemented``. Numeric methods and rich comparison methods may\n   return this value if they do not implement the operation for the\n   operands provided.  (The interpreter will then try the reflected\n   operation, or some other fallback, depending on the operator.)  Its\n   truth value is true.\n\nEllipsis\n   This type has a single value.  There is a single object with this\n   value. This object is accessed through the built-in name\n   ``Ellipsis``. It is used to indicate the presence of the ``...``\n   syntax in a slice.  Its truth value is true.\n\n``numbers.Number``\n   These are created by numeric literals and returned as results by\n   arithmetic operators and arithmetic built-in functions.  Numeric\n   objects are immutable; once created their value never changes.\n   Python numbers are of course strongly related to mathematical\n   numbers, but subject to the limitations of numerical representation\n   in computers.\n\n   Python distinguishes between integers, floating point numbers, and\n   complex numbers:\n\n   ``numbers.Integral``\n      These represent elements from the mathematical set of integers\n      (positive and negative).\n\n      There are three types of integers:\n\n      Plain integers\n         These represent numbers in the range -2147483648 through\n         2147483647. (The range may be larger on machines with a\n         larger natural word size, but not smaller.)  When the result\n         of an operation would fall outside this range, the result is\n         normally returned as a long integer (in some cases, the\n         exception ``OverflowError`` is raised instead).  For the\n         purpose of shift and mask operations, integers are assumed to\n         have a binary, 2\'s complement notation using 32 or more bits,\n         and hiding no bits from the user (i.e., all 4294967296\n         different bit patterns correspond to different values).\n\n      Long integers\n         These represent numbers in an unlimited range, subject to\n         available (virtual) memory only.  For the purpose of shift\n         and mask operations, a binary representation is assumed, and\n         negative numbers are represented in a variant of 2\'s\n         complement which gives the illusion of an infinite string of\n         sign bits extending to the left.\n\n      Booleans\n         These represent the truth values False and True.  The two\n         objects representing the values ``False`` and ``True`` are\n         the only Boolean objects. The Boolean type is a subtype of\n         plain integers, and Boolean values behave like the values 0\n         and 1, respectively, in almost all contexts, the exception\n         being that when converted to a string, the strings\n         ``"False"`` or ``"True"`` are returned, respectively.\n\n      The rules for integer representation are intended to give the\n      most meaningful interpretation of shift and mask operations\n      involving negative integers and the least surprises when\n      switching between the plain and long integer domains.  Any\n      operation, if it yields a result in the plain integer domain,\n      will yield the same result in the long integer domain or when\n      using mixed operands.  The switch between domains is transparent\n      to the programmer.\n\n   ``numbers.Real`` (``float``)\n      These represent machine-level double precision floating point\n      numbers. You are at the mercy of the underlying machine\n      architecture (and C or Java implementation) for the accepted\n      range and handling of overflow. Python does not support single-\n      precision floating point numbers; the savings in processor and\n      memory usage that are usually the reason for using these is\n      dwarfed by the overhead of using objects in Python, so there is\n      no reason to complicate the language with two kinds of floating\n      point numbers.\n\n   ``numbers.Complex``\n      These represent complex numbers as a pair of machine-level\n      double precision floating point numbers.  The same caveats apply\n      as for floating point numbers. The real and imaginary parts of a\n      complex number ``z`` can be retrieved through the read-only\n      attributes ``z.real`` and ``z.imag``.\n\nSequences\n   These represent finite ordered sets indexed by non-negative\n   numbers. The built-in function ``len()`` returns the number of\n   items of a sequence. When the length of a sequence is *n*, the\n   index set contains the numbers 0, 1, ..., *n*-1.  Item *i* of\n   sequence *a* is selected by ``a[i]``.\n\n   Sequences also support slicing: ``a[i:j]`` selects all items with\n   index *k* such that *i* ``<=`` *k* ``<`` *j*.  When used as an\n   expression, a slice is a sequence of the same type.  This implies\n   that the index set is renumbered so that it starts at 0.\n\n   Some sequences also support "extended slicing" with a third "step"\n   parameter: ``a[i:j:k]`` selects all items of *a* with index *x*\n   where ``x = i + n*k``, *n* ``>=`` ``0`` and *i* ``<=`` *x* ``<``\n   *j*.\n\n   Sequences are distinguished according to their mutability:\n\n   Immutable sequences\n      An object of an immutable sequence type cannot change once it is\n      created.  (If the object contains references to other objects,\n      these other objects may be mutable and may be changed; however,\n      the collection of objects directly referenced by an immutable\n      object cannot change.)\n\n      The following types are immutable sequences:\n\n      Strings\n         The items of a string are characters.  There is no separate\n         character type; a character is represented by a string of one\n         item. Characters represent (at least) 8-bit bytes.  The\n         built-in functions ``chr()`` and ``ord()`` convert between\n         characters and nonnegative integers representing the byte\n         values.  Bytes with the values 0-127 usually represent the\n         corresponding ASCII values, but the interpretation of values\n         is up to the program.  The string data type is also used to\n         represent arrays of bytes, e.g., to hold data read from a\n         file.\n\n         (On systems whose native character set is not ASCII, strings\n         may use EBCDIC in their internal representation, provided the\n         functions ``chr()`` and ``ord()`` implement a mapping between\n         ASCII and EBCDIC, and string comparison preserves the ASCII\n         order. Or perhaps someone can propose a better rule?)\n\n      Unicode\n         The items of a Unicode object are Unicode code units.  A\n         Unicode code unit is represented by a Unicode object of one\n         item and can hold either a 16-bit or 32-bit value\n         representing a Unicode ordinal (the maximum value for the\n         ordinal is given in ``sys.maxunicode``, and depends on how\n         Python is configured at compile time).  Surrogate pairs may\n         be present in the Unicode object, and will be reported as two\n         separate items.  The built-in functions ``unichr()`` and\n         ``ord()`` convert between code units and nonnegative integers\n         representing the Unicode ordinals as defined in the Unicode\n         Standard 3.0. Conversion from and to other encodings are\n         possible through the Unicode method ``encode()`` and the\n         built-in function ``unicode()``.\n\n      Tuples\n         The items of a tuple are arbitrary Python objects. Tuples of\n         two or more items are formed by comma-separated lists of\n         expressions.  A tuple of one item (a \'singleton\') can be\n         formed by affixing a comma to an expression (an expression by\n         itself does not create a tuple, since parentheses must be\n         usable for grouping of expressions).  An empty tuple can be\n         formed by an empty pair of parentheses.\n\n   Mutable sequences\n      Mutable sequences can be changed after they are created.  The\n      subscription and slicing notations can be used as the target of\n      assignment and ``del`` (delete) statements.\n\n      There are currently two intrinsic mutable sequence types:\n\n      Lists\n         The items of a list are arbitrary Python objects.  Lists are\n         formed by placing a comma-separated list of expressions in\n         square brackets. (Note that there are no special cases needed\n         to form lists of length 0 or 1.)\n\n      Byte Arrays\n         A bytearray object is a mutable array. They are created by\n         the built-in ``bytearray()`` constructor.  Aside from being\n         mutable (and hence unhashable), byte arrays otherwise provide\n         the same interface and functionality as immutable bytes\n         objects.\n\n      The extension module ``array`` provides an additional example of\n      a mutable sequence type.\n\nSet types\n   These represent unordered, finite sets of unique, immutable\n   objects. As such, they cannot be indexed by any subscript. However,\n   they can be iterated over, and the built-in function ``len()``\n   returns the number of items in a set. Common uses for sets are fast\n   membership testing, removing duplicates from a sequence, and\n   computing mathematical operations such as intersection, union,\n   difference, and symmetric difference.\n\n   For set elements, the same immutability rules apply as for\n   dictionary keys. Note that numeric types obey the normal rules for\n   numeric comparison: if two numbers compare equal (e.g., ``1`` and\n   ``1.0``), only one of them can be contained in a set.\n\n   There are currently two intrinsic set types:\n\n   Sets\n      These represent a mutable set. They are created by the built-in\n      ``set()`` constructor and can be modified afterwards by several\n      methods, such as ``add()``.\n\n   Frozen sets\n      These represent an immutable set.  They are created by the\n      built-in ``frozenset()`` constructor.  As a frozenset is\n      immutable and *hashable*, it can be used again as an element of\n      another set, or as a dictionary key.\n\nMappings\n   These represent finite sets of objects indexed by arbitrary index\n   sets. The subscript notation ``a[k]`` selects the item indexed by\n   ``k`` from the mapping ``a``; this can be used in expressions and\n   as the target of assignments or ``del`` statements. The built-in\n   function ``len()`` returns the number of items in a mapping.\n\n   There is currently a single intrinsic mapping type:\n\n   Dictionaries\n      These represent finite sets of objects indexed by nearly\n      arbitrary values.  The only types of values not acceptable as\n      keys are values containing lists or dictionaries or other\n      mutable types that are compared by value rather than by object\n      identity, the reason being that the efficient implementation of\n      dictionaries requires a key\'s hash value to remain constant.\n      Numeric types used for keys obey the normal rules for numeric\n      comparison: if two numbers compare equal (e.g., ``1`` and\n      ``1.0``) then they can be used interchangeably to index the same\n      dictionary entry.\n\n      Dictionaries are mutable; they can be created by the ``{...}``\n      notation (see section *Dictionary displays*).\n\n      The extension modules ``dbm``, ``gdbm``, and ``bsddb`` provide\n      additional examples of mapping types.\n\nCallable types\n   These are the types to which the function call operation (see\n   section *Calls*) can be applied:\n\n   User-defined functions\n      A user-defined function object is created by a function\n      definition (see section *Function definitions*).  It should be\n      called with an argument list containing the same number of items\n      as the function\'s formal parameter list.\n\n      Special attributes:\n\n      +-------------------------+---------------------------------+-------------+\n      | Attribute               | Meaning                         |             |\n      +=========================+=================================+=============+\n      | ``__doc__``             | The function\'s documentation    | Writable    |\n      | ``func_doc``            | string, or ``None`` if          |             |\n      |                         | unavailable.                    |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__name__``            | The function\'s name.            | Writable    |\n      | ``func_name``           |                                 |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__module__``          | The name of the module the      | Writable    |\n      |                         | function was defined in, or     |             |\n      |                         | ``None`` if unavailable.        |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__defaults__``        | A tuple containing default      | Writable    |\n      | ``func_defaults``       | argument values for those       |             |\n      |                         | arguments that have defaults,   |             |\n      |                         | or ``None`` if no arguments     |             |\n      |                         | have a default value.           |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__code__``            | The code object representing    | Writable    |\n      | ``func_code``           | the compiled function body.     |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__globals__``         | A reference to the dictionary   | Read-only   |\n      | ``func_globals``        | that holds the function\'s       |             |\n      |                         | global variables --- the global |             |\n      |                         | namespace of the module in      |             |\n      |                         | which the function was defined. |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__dict__``            | The namespace supporting        | Writable    |\n      | ``func_dict``           | arbitrary function attributes.  |             |\n      +-------------------------+---------------------------------+-------------+\n      | ``__closure__``         | ``None`` or a tuple of cells    | Read-only   |\n      | ``func_closure``        | that contain bindings for the   |             |\n      |                         | function\'s free variables.      |             |\n      +-------------------------+---------------------------------+-------------+\n\n      Most of the attributes labelled "Writable" check the type of the\n      assigned value.\n\n      Changed in version 2.4: ``func_name`` is now writable.\n\n      Changed in version 2.6: The double-underscore attributes\n      ``__closure__``, ``__code__``, ``__defaults__``, and\n      ``__globals__`` were introduced as aliases for the corresponding\n      ``func_*`` attributes for forwards compatibility with Python 3.\n\n      Function objects also support getting and setting arbitrary\n      attributes, which can be used, for example, to attach metadata\n      to functions.  Regular attribute dot-notation is used to get and\n      set such attributes. *Note that the current implementation only\n      supports function attributes on user-defined functions. Function\n      attributes on built-in functions may be supported in the\n      future.*\n\n      Additional information about a function\'s definition can be\n      retrieved from its code object; see the description of internal\n      types below.\n\n   User-defined methods\n      A user-defined method object combines a class, a class instance\n      (or ``None``) and any callable object (normally a user-defined\n      function).\n\n      Special read-only attributes: ``im_self`` is the class instance\n      object, ``im_func`` is the function object; ``im_class`` is the\n      class of ``im_self`` for bound methods or the class that asked\n      for the method for unbound methods; ``__doc__`` is the method\'s\n      documentation (same as ``im_func.__doc__``); ``__name__`` is the\n      method name (same as ``im_func.__name__``); ``__module__`` is\n      the name of the module the method was defined in, or ``None`` if\n      unavailable.\n\n      Changed in version 2.2: ``im_self`` used to refer to the class\n      that defined the method.\n\n      Changed in version 2.6: For Python 3 forward-compatibility,\n      ``im_func`` is also available as ``__func__``, and ``im_self``\n      as ``__self__``.\n\n      Methods also support accessing (but not setting) the arbitrary\n      function attributes on the underlying function object.\n\n      User-defined method objects may be created when getting an\n      attribute of a class (perhaps via an instance of that class), if\n      that attribute is a user-defined function object, an unbound\n      user-defined method object, or a class method object. When the\n      attribute is a user-defined method object, a new method object\n      is only created if the class from which it is being retrieved is\n      the same as, or a derived class of, the class stored in the\n      original method object; otherwise, the original method object is\n      used as it is.\n\n      When a user-defined method object is created by retrieving a\n      user-defined function object from a class, its ``im_self``\n      attribute is ``None`` and the method object is said to be\n      unbound. When one is created by retrieving a user-defined\n      function object from a class via one of its instances, its\n      ``im_self`` attribute is the instance, and the method object is\n      said to be bound. In either case, the new method\'s ``im_class``\n      attribute is the class from which the retrieval takes place, and\n      its ``im_func`` attribute is the original function object.\n\n      When a user-defined method object is created by retrieving\n      another method object from a class or instance, the behaviour is\n      the same as for a function object, except that the ``im_func``\n      attribute of the new instance is not the original method object\n      but its ``im_func`` attribute.\n\n      When a user-defined method object is created by retrieving a\n      class method object from a class or instance, its ``im_self``\n      attribute is the class itself, and its ``im_func`` attribute is\n      the function object underlying the class method.\n\n      When an unbound user-defined method object is called, the\n      underlying function (``im_func``) is called, with the\n      restriction that the first argument must be an instance of the\n      proper class (``im_class``) or of a derived class thereof.\n\n      When a bound user-defined method object is called, the\n      underlying function (``im_func``) is called, inserting the class\n      instance (``im_self``) in front of the argument list.  For\n      instance, when ``C`` is a class which contains a definition for\n      a function ``f()``, and ``x`` is an instance of ``C``, calling\n      ``x.f(1)`` is equivalent to calling ``C.f(x, 1)``.\n\n      When a user-defined method object is derived from a class method\n      object, the "class instance" stored in ``im_self`` will actually\n      be the class itself, so that calling either ``x.f(1)`` or\n      ``C.f(1)`` is equivalent to calling ``f(C,1)`` where ``f`` is\n      the underlying function.\n\n      Note that the transformation from function object to (unbound or\n      bound) method object happens each time the attribute is\n      retrieved from the class or instance. In some cases, a fruitful\n      optimization is to assign the attribute to a local variable and\n      call that local variable. Also notice that this transformation\n      only happens for user-defined functions; other callable objects\n      (and all non-callable objects) are retrieved without\n      transformation.  It is also important to note that user-defined\n      functions which are attributes of a class instance are not\n      converted to bound methods; this *only* happens when the\n      function is an attribute of the class.\n\n   Generator functions\n      A function or method which uses the ``yield`` statement (see\n      section *The yield statement*) is called a *generator function*.\n      Such a function, when called, always returns an iterator object\n      which can be used to execute the body of the function:  calling\n      the iterator\'s ``next()`` method will cause the function to\n      execute until it provides a value using the ``yield`` statement.\n      When the function executes a ``return`` statement or falls off\n      the end, a ``StopIteration`` exception is raised and the\n      iterator will have reached the end of the set of values to be\n      returned.\n\n   Built-in functions\n      A built-in function object is a wrapper around a C function.\n      Examples of built-in functions are ``len()`` and ``math.sin()``\n      (``math`` is a standard built-in module). The number and type of\n      the arguments are determined by the C function. Special read-\n      only attributes: ``__doc__`` is the function\'s documentation\n      string, or ``None`` if unavailable; ``__name__`` is the\n      function\'s name; ``__self__`` is set to ``None`` (but see the\n      next item); ``__module__`` is the name of the module the\n      function was defined in or ``None`` if unavailable.\n\n   Built-in methods\n      This is really a different disguise of a built-in function, this\n      time containing an object passed to the C function as an\n      implicit extra argument.  An example of a built-in method is\n      ``alist.append()``, assuming *alist* is a list object. In this\n      case, the special read-only attribute ``__self__`` is set to the\n      object denoted by *alist*.\n\n   Class Types\n      Class types, or "new-style classes," are callable.  These\n      objects normally act as factories for new instances of\n      themselves, but variations are possible for class types that\n      override ``__new__()``.  The arguments of the call are passed to\n      ``__new__()`` and, in the typical case, to ``__init__()`` to\n      initialize the new instance.\n\n   Classic Classes\n      Class objects are described below.  When a class object is\n      called, a new class instance (also described below) is created\n      and returned.  This implies a call to the class\'s ``__init__()``\n      method if it has one.  Any arguments are passed on to the\n      ``__init__()`` method.  If there is no ``__init__()`` method,\n      the class must be called without arguments.\n\n   Class instances\n      Class instances are described below.  Class instances are\n      callable only when the class has a ``__call__()`` method;\n      ``x(arguments)`` is a shorthand for ``x.__call__(arguments)``.\n\nModules\n   Modules are imported by the ``import`` statement (see section *The\n   import statement*). A module object has a namespace implemented by\n   a dictionary object (this is the dictionary referenced by the\n   func_globals attribute of functions defined in the module).\n   Attribute references are translated to lookups in this dictionary,\n   e.g., ``m.x`` is equivalent to ``m.__dict__["x"]``. A module object\n   does not contain the code object used to initialize the module\n   (since it isn\'t needed once the initialization is done).\n\n   Attribute assignment updates the module\'s namespace dictionary,\n   e.g., ``m.x = 1`` is equivalent to ``m.__dict__["x"] = 1``.\n\n   Special read-only attribute: ``__dict__`` is the module\'s namespace\n   as a dictionary object.\n\n   **CPython implementation detail:** Because of the way CPython\n   clears module dictionaries, the module dictionary will be cleared\n   when the module falls out of scope even if the dictionary still has\n   live references.  To avoid this, copy the dictionary or keep the\n   module around while using its dictionary directly.\n\n   Predefined (writable) attributes: ``__name__`` is the module\'s\n   name; ``__doc__`` is the module\'s documentation string, or ``None``\n   if unavailable; ``__file__`` is the pathname of the file from which\n   the module was loaded, if it was loaded from a file. The\n   ``__file__`` attribute is not present for C modules that are\n   statically linked into the interpreter; for extension modules\n   loaded dynamically from a shared library, it is the pathname of the\n   shared library file.\n\nClasses\n   Both class types (new-style classes) and class objects (old-\n   style/classic classes) are typically created by class definitions\n   (see section *Class definitions*).  A class has a namespace\n   implemented by a dictionary object. Class attribute references are\n   translated to lookups in this dictionary, e.g., ``C.x`` is\n   translated to ``C.__dict__["x"]`` (although for new-style classes\n   in particular there are a number of hooks which allow for other\n   means of locating attributes). When the attribute name is not found\n   there, the attribute search continues in the base classes.  For\n   old-style classes, the search is depth-first, left-to-right in the\n   order of occurrence in the base class list. New-style classes use\n   the more complex C3 method resolution order which behaves correctly\n   even in the presence of \'diamond\' inheritance structures where\n   there are multiple inheritance paths leading back to a common\n   ancestor. Additional details on the C3 MRO used by new-style\n   classes can be found in the documentation accompanying the 2.3\n   release at http://www.python.org/download/releases/2.3/mro/.\n\n   When a class attribute reference (for class ``C``, say) would yield\n   a user-defined function object or an unbound user-defined method\n   object whose associated class is either ``C`` or one of its base\n   classes, it is transformed into an unbound user-defined method\n   object whose ``im_class`` attribute is ``C``. When it would yield a\n   class method object, it is transformed into a bound user-defined\n   method object whose ``im_self`` attribute is ``C``.  When it would\n   yield a static method object, it is transformed into the object\n   wrapped by the static method object. See section *Implementing\n   Descriptors* for another way in which attributes retrieved from a\n   class may differ from those actually contained in its ``__dict__``\n   (note that only new-style classes support descriptors).\n\n   Class attribute assignments update the class\'s dictionary, never\n   the dictionary of a base class.\n\n   A class object can be called (see above) to yield a class instance\n   (see below).\n\n   Special attributes: ``__name__`` is the class name; ``__module__``\n   is the module name in which the class was defined; ``__dict__`` is\n   the dictionary containing the class\'s namespace; ``__bases__`` is a\n   tuple (possibly empty or a singleton) containing the base classes,\n   in the order of their occurrence in the base class list;\n   ``__doc__`` is the class\'s documentation string, or None if\n   undefined.\n\nClass instances\n   A class instance is created by calling a class object (see above).\n   A class instance has a namespace implemented as a dictionary which\n   is the first place in which attribute references are searched.\n   When an attribute is not found there, and the instance\'s class has\n   an attribute by that name, the search continues with the class\n   attributes.  If a class attribute is found that is a user-defined\n   function object or an unbound user-defined method object whose\n   associated class is the class (call it ``C``) of the instance for\n   which the attribute reference was initiated or one of its bases, it\n   is transformed into a bound user-defined method object whose\n   ``im_class`` attribute is ``C`` and whose ``im_self`` attribute is\n   the instance. Static method and class method objects are also\n   transformed, as if they had been retrieved from class ``C``; see\n   above under "Classes". See section *Implementing Descriptors* for\n   another way in which attributes of a class retrieved via its\n   instances may differ from the objects actually stored in the\n   class\'s ``__dict__``. If no class attribute is found, and the\n   object\'s class has a ``__getattr__()`` method, that is called to\n   satisfy the lookup.\n\n   Attribute assignments and deletions update the instance\'s\n   dictionary, never a class\'s dictionary.  If the class has a\n   ``__setattr__()`` or ``__delattr__()`` method, this is called\n   instead of updating the instance dictionary directly.\n\n   Class instances can pretend to be numbers, sequences, or mappings\n   if they have methods with certain special names.  See section\n   *Special method names*.\n\n   Special attributes: ``__dict__`` is the attribute dictionary;\n   ``__class__`` is the instance\'s class.\n\nFiles\n   A file object represents an open file.  File objects are created by\n   the ``open()`` built-in function, and also by ``os.popen()``,\n   ``os.fdopen()``, and the ``makefile()`` method of socket objects\n   (and perhaps by other functions or methods provided by extension\n   modules).  The objects ``sys.stdin``, ``sys.stdout`` and\n   ``sys.stderr`` are initialized to file objects corresponding to the\n   interpreter\'s standard input, output and error streams.  See *File\n   Objects* for complete documentation of file objects.\n\nInternal types\n   A few types used internally by the interpreter are exposed to the\n   user. Their definitions may change with future versions of the\n   interpreter, but they are mentioned here for completeness.\n\n   Code objects\n      Code objects represent *byte-compiled* executable Python code,\n      or *bytecode*. The difference between a code object and a\n      function object is that the function object contains an explicit\n      reference to the function\'s globals (the module in which it was\n      defined), while a code object contains no context; also the\n      default argument values are stored in the function object, not\n      in the code object (because they represent values calculated at\n      run-time).  Unlike function objects, code objects are immutable\n      and contain no references (directly or indirectly) to mutable\n      objects.\n\n      Special read-only attributes: ``co_name`` gives the function\n      name; ``co_argcount`` is the number of positional arguments\n      (including arguments with default values); ``co_nlocals`` is the\n      number of local variables used by the function (including\n      arguments); ``co_varnames`` is a tuple containing the names of\n      the local variables (starting with the argument names);\n      ``co_cellvars`` is a tuple containing the names of local\n      variables that are referenced by nested functions;\n      ``co_freevars`` is a tuple containing the names of free\n      variables; ``co_code`` is a string representing the sequence of\n      bytecode instructions; ``co_consts`` is a tuple containing the\n      literals used by the bytecode; ``co_names`` is a tuple\n      containing the names used by the bytecode; ``co_filename`` is\n      the filename from which the code was compiled;\n      ``co_firstlineno`` is the first line number of the function;\n      ``co_lnotab`` is a string encoding the mapping from bytecode\n      offsets to line numbers (for details see the source code of the\n      interpreter); ``co_stacksize`` is the required stack size\n      (including local variables); ``co_flags`` is an integer encoding\n      a number of flags for the interpreter.\n\n      The following flag bits are defined for ``co_flags``: bit\n      ``0x04`` is set if the function uses the ``*arguments`` syntax\n      to accept an arbitrary number of positional arguments; bit\n      ``0x08`` is set if the function uses the ``**keywords`` syntax\n      to accept arbitrary keyword arguments; bit ``0x20`` is set if\n      the function is a generator.\n\n      Future feature declarations (``from __future__ import\n      division``) also use bits in ``co_flags`` to indicate whether a\n      code object was compiled with a particular feature enabled: bit\n      ``0x2000`` is set if the function was compiled with future\n      division enabled; bits ``0x10`` and ``0x1000`` were used in\n      earlier versions of Python.\n\n      Other bits in ``co_flags`` are reserved for internal use.\n\n      If a code object represents a function, the first item in\n      ``co_consts`` is the documentation string of the function, or\n      ``None`` if undefined.\n\n   Frame objects\n      Frame objects represent execution frames.  They may occur in\n      traceback objects (see below).\n\n      Special read-only attributes: ``f_back`` is to the previous\n      stack frame (towards the caller), or ``None`` if this is the\n      bottom stack frame; ``f_code`` is the code object being executed\n      in this frame; ``f_locals`` is the dictionary used to look up\n      local variables; ``f_globals`` is used for global variables;\n      ``f_builtins`` is used for built-in (intrinsic) names;\n      ``f_restricted`` is a flag indicating whether the function is\n      executing in restricted execution mode; ``f_lasti`` gives the\n      precise instruction (this is an index into the bytecode string\n      of the code object).\n\n      Special writable attributes: ``f_trace``, if not ``None``, is a\n      function called at the start of each source code line (this is\n      used by the debugger); ``f_exc_type``, ``f_exc_value``,\n      ``f_exc_traceback`` represent the last exception raised in the\n      parent frame provided another exception was ever raised in the\n      current frame (in all other cases they are None); ``f_lineno``\n      is the current line number of the frame --- writing to this from\n      within a trace function jumps to the given line (only for the\n      bottom-most frame).  A debugger can implement a Jump command\n      (aka Set Next Statement) by writing to f_lineno.\n\n   Traceback objects\n      Traceback objects represent a stack trace of an exception.  A\n      traceback object is created when an exception occurs.  When the\n      search for an exception handler unwinds the execution stack, at\n      each unwound level a traceback object is inserted in front of\n      the current traceback.  When an exception handler is entered,\n      the stack trace is made available to the program. (See section\n      *The try statement*.) It is accessible as ``sys.exc_traceback``,\n      and also as the third item of the tuple returned by\n      ``sys.exc_info()``.  The latter is the preferred interface,\n      since it works correctly when the program is using multiple\n      threads. When the program contains no suitable handler, the\n      stack trace is written (nicely formatted) to the standard error\n      stream; if the interpreter is interactive, it is also made\n      available to the user as ``sys.last_traceback``.\n\n      Special read-only attributes: ``tb_next`` is the next level in\n      the stack trace (towards the frame where the exception\n      occurred), or ``None`` if there is no next level; ``tb_frame``\n      points to the execution frame of the current level;\n      ``tb_lineno`` gives the line number where the exception\n      occurred; ``tb_lasti`` indicates the precise instruction.  The\n      line number and last instruction in the traceback may differ\n      from the line number of its frame object if the exception\n      occurred in a ``try`` statement with no matching except clause\n      or with a finally clause.\n\n   Slice objects\n      Slice objects are used to represent slices when *extended slice\n      syntax* is used. This is a slice using two colons, or multiple\n      slices or ellipses separated by commas, e.g., ``a[i:j:step]``,\n      ``a[i:j, k:l]``, or ``a[..., i:j]``.  They are also created by\n      the built-in ``slice()`` function.\n\n      Special read-only attributes: ``start`` is the lower bound;\n      ``stop`` is the upper bound; ``step`` is the step value; each is\n      ``None`` if omitted.  These attributes can have any type.\n\n      Slice objects support one method:\n\n      slice.indices(self, length)\n\n         This method takes a single integer argument *length* and\n         computes information about the extended slice that the slice\n         object would describe if applied to a sequence of *length*\n         items.  It returns a tuple of three integers; respectively\n         these are the *start* and *stop* indices and the *step* or\n         stride length of the slice. Missing or out-of-bounds indices\n         are handled in a manner consistent with regular slices.\n\n         New in version 2.3.\n\n   Static method objects\n      Static method objects provide a way of defeating the\n      transformation of function objects to method objects described\n      above. A static method object is a wrapper around any other\n      object, usually a user-defined method object. When a static\n      method object is retrieved from a class or a class instance, the\n      object actually returned is the wrapped object, which is not\n      subject to any further transformation. Static method objects are\n      not themselves callable, although the objects they wrap usually\n      are. Static method objects are created by the built-in\n      ``staticmethod()`` constructor.\n\n   Class method objects\n      A class method object, like a static method object, is a wrapper\n      around another object that alters the way in which that object\n      is retrieved from classes and class instances. The behaviour of\n      class method objects upon such retrieval is described above,\n      under "User-defined methods". Class method objects are created\n      by the built-in ``classmethod()`` constructor.\n',
  'typesfunctions': '\nFunctions\n*********\n\nFunction objects are created by function definitions.  The only\noperation on a function object is to call it: ``func(argument-list)``.\n\nThere are really two flavors of function objects: built-in functions\nand user-defined functions.  Both support the same operation (to call\nthe function), but the implementation is different, hence the\ndifferent object types.\n\nSee *Function definitions* for more information.\n',
- 'typesmapping': '\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects.  There is currently only one standard\nmapping type, the *dictionary*.  (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values.  Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys.  Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry.  (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass class dict(**kwarg)\nclass class dict(mapping, **kwarg)\nclass class dict(iterable, **kwarg)\n\n   Return a new dictionary initialized from an optional positional\n   argument and a possibly empty set of keyword arguments.\n\n   If no positional argument is given, an empty dictionary is created.\n   If a positional argument is given and it is a mapping object, a\n   dictionary is created with the same key-value pairs as the mapping\n   object.  Otherwise, the positional argument must be an *iterator*\n   object.  Each item in the iterable must itself be an iterator with\n   exactly two objects.  The first object of each item becomes a key\n   in the new dictionary, and the second object the corresponding\n   value.  If a key occurs more than once, the last value for that key\n   becomes the corresponding value in the new dictionary.\n\n   If keyword arguments are given, the keyword arguments and their\n   values are added to the dictionary created from the positional\n   argument.  If a key being added is already present, the value from\n   the keyword argument replaces the value from the positional\n   argument.\n\n   To illustrate, the following examples all return a dictionary equal\n   to ``{"one": 1, "two": 2, "three": 3}``:\n\n      >>> a = dict(one=1, two=2, three=3)\n      >>> b = {\'one\': 1, \'two\': 2, \'three\': 3}\n      >>> c = dict(zip([\'one\', \'two\', \'three\'], [1, 2, 3]))\n      >>> d = dict([(\'two\', 2), (\'one\', 1), (\'three\', 3)])\n      >>> e = dict({\'three\': 3, \'one\': 1, \'two\': 2})\n      >>> a == b == c == d == e\n      True\n\n   Providing keyword arguments as in the first example only works for\n   keys that are valid Python identifiers.  Otherwise, any valid keys\n   can be used.\n\n   New in version 2.2.\n\n   Changed in version 2.3: Support for building a dictionary from\n   keyword arguments added.\n\n   These are the operations that dictionaries support (and therefore,\n   custom mapping types should support too):\n\n   len(d)\n\n      Return the number of items in the dictionary *d*.\n\n   d[key]\n\n      Return the item of *d* with key *key*.  Raises a ``KeyError`` if\n      *key* is not in the map.\n\n      New in version 2.5: If a subclass of dict defines a method\n      ``__missing__()``, if the key *key* is not present, the\n      ``d[key]`` operation calls that method with the key *key* as\n      argument.  The ``d[key]`` operation then returns or raises\n      whatever is returned or raised by the ``__missing__(key)`` call\n      if the key is not present. No other operations or methods invoke\n      ``__missing__()``. If ``__missing__()`` is not defined,\n      ``KeyError`` is raised.  ``__missing__()`` must be a method; it\n      cannot be an instance variable. For an example, see\n      ``collections.defaultdict``.\n\n   d[key] = value\n\n      Set ``d[key]`` to *value*.\n\n   del d[key]\n\n      Remove ``d[key]`` from *d*.  Raises a ``KeyError`` if *key* is\n      not in the map.\n\n   key in d\n\n      Return ``True`` if *d* has a key *key*, else ``False``.\n\n      New in version 2.2.\n\n   key not in d\n\n      Equivalent to ``not key in d``.\n\n      New in version 2.2.\n\n   iter(d)\n\n      Return an iterator over the keys of the dictionary.  This is a\n      shortcut for ``iterkeys()``.\n\n   clear()\n\n      Remove all items from the dictionary.\n\n   copy()\n\n      Return a shallow copy of the dictionary.\n\n   fromkeys(seq[, value])\n\n      Create a new dictionary with keys from *seq* and values set to\n      *value*.\n\n      ``fromkeys()`` is a class method that returns a new dictionary.\n      *value* defaults to ``None``.\n\n      New in version 2.3.\n\n   get(key[, default])\n\n      Return the value for *key* if *key* is in the dictionary, else\n      *default*. If *default* is not given, it defaults to ``None``,\n      so that this method never raises a ``KeyError``.\n\n   has_key(key)\n\n      Test for the presence of *key* in the dictionary.  ``has_key()``\n      is deprecated in favor of ``key in d``.\n\n   items()\n\n      Return a copy of the dictionary\'s list of ``(key, value)``\n      pairs.\n\n      **CPython implementation detail:** Keys and values are listed in\n      an arbitrary order which is non-random, varies across Python\n      implementations, and depends on the dictionary\'s history of\n      insertions and deletions.\n\n      If ``items()``, ``keys()``, ``values()``, ``iteritems()``,\n      ``iterkeys()``, and ``itervalues()`` are called with no\n      intervening modifications to the dictionary, the lists will\n      directly correspond.  This allows the creation of ``(value,\n      key)`` pairs using ``zip()``: ``pairs = zip(d.values(),\n      d.keys())``.  The same relationship holds for the ``iterkeys()``\n      and ``itervalues()`` methods: ``pairs = zip(d.itervalues(),\n      d.iterkeys())`` provides the same value for ``pairs``. Another\n      way to create the same list is ``pairs = [(v, k) for (k, v) in\n      d.iteritems()]``.\n\n   iteritems()\n\n      Return an iterator over the dictionary\'s ``(key, value)`` pairs.\n      See the note for ``dict.items()``.\n\n      Using ``iteritems()`` while adding or deleting entries in the\n      dictionary may raise a ``RuntimeError`` or fail to iterate over\n      all entries.\n\n      New in version 2.2.\n\n   iterkeys()\n\n      Return an iterator over the dictionary\'s keys.  See the note for\n      ``dict.items()``.\n\n      Using ``iterkeys()`` while adding or deleting entries in the\n      dictionary may raise a ``RuntimeError`` or fail to iterate over\n      all entries.\n\n      New in version 2.2.\n\n   itervalues()\n\n      Return an iterator over the dictionary\'s values.  See the note\n      for ``dict.items()``.\n\n      Using ``itervalues()`` while adding or deleting entries in the\n      dictionary may raise a ``RuntimeError`` or fail to iterate over\n      all entries.\n\n      New in version 2.2.\n\n   keys()\n\n      Return a copy of the dictionary\'s list of keys.  See the note\n      for ``dict.items()``.\n\n   pop(key[, default])\n\n      If *key* is in the dictionary, remove it and return its value,\n      else return *default*.  If *default* is not given and *key* is\n      not in the dictionary, a ``KeyError`` is raised.\n\n      New in version 2.3.\n\n   popitem()\n\n      Remove and return an arbitrary ``(key, value)`` pair from the\n      dictionary.\n\n      ``popitem()`` is useful to destructively iterate over a\n      dictionary, as often used in set algorithms.  If the dictionary\n      is empty, calling ``popitem()`` raises a ``KeyError``.\n\n   setdefault(key[, default])\n\n      If *key* is in the dictionary, return its value.  If not, insert\n      *key* with a value of *default* and return *default*.  *default*\n      defaults to ``None``.\n\n   update([other])\n\n      Update the dictionary with the key/value pairs from *other*,\n      overwriting existing keys.  Return ``None``.\n\n      ``update()`` accepts either another dictionary object or an\n      iterable of key/value pairs (as tuples or other iterables of\n      length two).  If keyword arguments are specified, the dictionary\n      is then updated with those key/value pairs: ``d.update(red=1,\n      blue=2)``.\n\n      Changed in version 2.4: Allowed the argument to be an iterable\n      of key/value pairs and allowed keyword arguments.\n\n   values()\n\n      Return a copy of the dictionary\'s list of values.  See the note\n      for ``dict.items()``.\n\n   viewitems()\n\n      Return a new view of the dictionary\'s items (``(key, value)``\n      pairs).  See below for documentation of view objects.\n\n      New in version 2.7.\n\n   viewkeys()\n\n      Return a new view of the dictionary\'s keys.  See below for\n      documentation of view objects.\n\n      New in version 2.7.\n\n   viewvalues()\n\n      Return a new view of the dictionary\'s values.  See below for\n      documentation of view objects.\n\n      New in version 2.7.\n\n\nDictionary view objects\n=======================\n\nThe objects returned by ``dict.viewkeys()``, ``dict.viewvalues()`` and\n``dict.viewitems()`` are *view objects*.  They provide a dynamic view\non the dictionary\'s entries, which means that when the dictionary\nchanges, the view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n   Return the number of entries in the dictionary.\n\niter(dictview)\n\n   Return an iterator over the keys, values or items (represented as\n   tuples of ``(key, value)``) in the dictionary.\n\n   Keys and values are iterated over in an arbitrary order which is\n   non-random, varies across Python implementations, and depends on\n   the dictionary\'s history of insertions and deletions. If keys,\n   values and items views are iterated over with no intervening\n   modifications to the dictionary, the order of items will directly\n   correspond.  This allows the creation of ``(value, key)`` pairs\n   using ``zip()``: ``pairs = zip(d.values(), d.keys())``.  Another\n   way to create the same list is ``pairs = [(v, k) for (k, v) in\n   d.items()]``.\n\n   Iterating views while adding or deleting entries in the dictionary\n   may raise a ``RuntimeError`` or fail to iterate over all entries.\n\nx in dictview\n\n   Return ``True`` if *x* is in the underlying dictionary\'s keys,\n   values or items (in the latter case, *x* should be a ``(key,\n   value)`` tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that (key, value) pairs are unique and\nhashable, then the items view is also set-like.  (Values views are not\ntreated as set-like since the entries are generally not unique.)  Then\nthese set operations are available ("other" refers either to another\nview or a set):\n\ndictview & other\n\n   Return the intersection of the dictview and the other object as a\n   new set.\n\ndictview | other\n\n   Return the union of the dictview and the other object as a new set.\n\ndictview - other\n\n   Return the difference between the dictview and the other object\n   (all elements in *dictview* that aren\'t in *other*) as a new set.\n\ndictview ^ other\n\n   Return the symmetric difference (all elements either in *dictview*\n   or *other*, but not in both) of the dictview and the other object\n   as a new set.\n\nAn example of dictionary view usage:\n\n   >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n   >>> keys = dishes.viewkeys()\n   >>> values = dishes.viewvalues()\n\n   >>> # iteration\n   >>> n = 0\n   >>> for val in values:\n   ...     n += val\n   >>> print(n)\n   504\n\n   >>> # keys and values are iterated over in the same order\n   >>> list(keys)\n   [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n   >>> list(values)\n   [2, 1, 1, 500]\n\n   >>> # view objects are dynamic and reflect dict changes\n   >>> del dishes[\'eggs\']\n   >>> del dishes[\'sausage\']\n   >>> list(keys)\n   [\'spam\', \'bacon\']\n\n   >>> # set operations\n   >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n   {\'bacon\'}\n',
+ 'typesmapping': '\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects.  There is currently only one standard\nmapping type, the *dictionary*.  (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values.  Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys.  Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry.  (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass class dict(**kwarg)\nclass class dict(mapping, **kwarg)\nclass class dict(iterable, **kwarg)\n\n   Return a new dictionary initialized from an optional positional\n   argument and a possibly empty set of keyword arguments.\n\n   If no positional argument is given, an empty dictionary is created.\n   If a positional argument is given and it is a mapping object, a\n   dictionary is created with the same key-value pairs as the mapping\n   object.  Otherwise, the positional argument must be an *iterable*\n   object.  Each item in the iterable must itself be an iterable with\n   exactly two objects.  The first object of each item becomes a key\n   in the new dictionary, and the second object the corresponding\n   value.  If a key occurs more than once, the last value for that key\n   becomes the corresponding value in the new dictionary.\n\n   If keyword arguments are given, the keyword arguments and their\n   values are added to the dictionary created from the positional\n   argument.  If a key being added is already present, the value from\n   the keyword argument replaces the value from the positional\n   argument.\n\n   To illustrate, the following examples all return a dictionary equal\n   to ``{"one": 1, "two": 2, "three": 3}``:\n\n      >>> a = dict(one=1, two=2, three=3)\n      >>> b = {\'one\': 1, \'two\': 2, \'three\': 3}\n      >>> c = dict(zip([\'one\', \'two\', \'three\'], [1, 2, 3]))\n      >>> d = dict([(\'two\', 2), (\'one\', 1), (\'three\', 3)])\n      >>> e = dict({\'three\': 3, \'one\': 1, \'two\': 2})\n      >>> a == b == c == d == e\n      True\n\n   Providing keyword arguments as in the first example only works for\n   keys that are valid Python identifiers.  Otherwise, any valid keys\n   can be used.\n\n   New in version 2.2.\n\n   Changed in version 2.3: Support for building a dictionary from\n   keyword arguments added.\n\n   These are the operations that dictionaries support (and therefore,\n   custom mapping types should support too):\n\n   len(d)\n\n      Return the number of items in the dictionary *d*.\n\n   d[key]\n\n      Return the item of *d* with key *key*.  Raises a ``KeyError`` if\n      *key* is not in the map.\n\n      New in version 2.5: If a subclass of dict defines a method\n      ``__missing__()``, if the key *key* is not present, the\n      ``d[key]`` operation calls that method with the key *key* as\n      argument.  The ``d[key]`` operation then returns or raises\n      whatever is returned or raised by the ``__missing__(key)`` call\n      if the key is not present. No other operations or methods invoke\n      ``__missing__()``. If ``__missing__()`` is not defined,\n      ``KeyError`` is raised.  ``__missing__()`` must be a method; it\n      cannot be an instance variable. For an example, see\n      ``collections.defaultdict``.\n\n   d[key] = value\n\n      Set ``d[key]`` to *value*.\n\n   del d[key]\n\n      Remove ``d[key]`` from *d*.  Raises a ``KeyError`` if *key* is\n      not in the map.\n\n   key in d\n\n      Return ``True`` if *d* has a key *key*, else ``False``.\n\n      New in version 2.2.\n\n   key not in d\n\n      Equivalent to ``not key in d``.\n\n      New in version 2.2.\n\n   iter(d)\n\n      Return an iterator over the keys of the dictionary.  This is a\n      shortcut for ``iterkeys()``.\n\n   clear()\n\n      Remove all items from the dictionary.\n\n   copy()\n\n      Return a shallow copy of the dictionary.\n\n   fromkeys(seq[, value])\n\n      Create a new dictionary with keys from *seq* and values set to\n      *value*.\n\n      ``fromkeys()`` is a class method that returns a new dictionary.\n      *value* defaults to ``None``.\n\n      New in version 2.3.\n\n   get(key[, default])\n\n      Return the value for *key* if *key* is in the dictionary, else\n      *default*. If *default* is not given, it defaults to ``None``,\n      so that this method never raises a ``KeyError``.\n\n   has_key(key)\n\n      Test for the presence of *key* in the dictionary.  ``has_key()``\n      is deprecated in favor of ``key in d``.\n\n   items()\n\n      Return a copy of the dictionary\'s list of ``(key, value)``\n      pairs.\n\n      **CPython implementation detail:** Keys and values are listed in\n      an arbitrary order which is non-random, varies across Python\n      implementations, and depends on the dictionary\'s history of\n      insertions and deletions.\n\n      If ``items()``, ``keys()``, ``values()``, ``iteritems()``,\n      ``iterkeys()``, and ``itervalues()`` are called with no\n      intervening modifications to the dictionary, the lists will\n      directly correspond.  This allows the creation of ``(value,\n      key)`` pairs using ``zip()``: ``pairs = zip(d.values(),\n      d.keys())``.  The same relationship holds for the ``iterkeys()``\n      and ``itervalues()`` methods: ``pairs = zip(d.itervalues(),\n      d.iterkeys())`` provides the same value for ``pairs``. Another\n      way to create the same list is ``pairs = [(v, k) for (k, v) in\n      d.iteritems()]``.\n\n   iteritems()\n\n      Return an iterator over the dictionary\'s ``(key, value)`` pairs.\n      See the note for ``dict.items()``.\n\n      Using ``iteritems()`` while adding or deleting entries in the\n      dictionary may raise a ``RuntimeError`` or fail to iterate over\n      all entries.\n\n      New in version 2.2.\n\n   iterkeys()\n\n      Return an iterator over the dictionary\'s keys.  See the note for\n      ``dict.items()``.\n\n      Using ``iterkeys()`` while adding or deleting entries in the\n      dictionary may raise a ``RuntimeError`` or fail to iterate over\n      all entries.\n\n      New in version 2.2.\n\n   itervalues()\n\n      Return an iterator over the dictionary\'s values.  See the note\n      for ``dict.items()``.\n\n      Using ``itervalues()`` while adding or deleting entries in the\n      dictionary may raise a ``RuntimeError`` or fail to iterate over\n      all entries.\n\n      New in version 2.2.\n\n   keys()\n\n      Return a copy of the dictionary\'s list of keys.  See the note\n      for ``dict.items()``.\n\n   pop(key[, default])\n\n      If *key* is in the dictionary, remove it and return its value,\n      else return *default*.  If *default* is not given and *key* is\n      not in the dictionary, a ``KeyError`` is raised.\n\n      New in version 2.3.\n\n   popitem()\n\n      Remove and return an arbitrary ``(key, value)`` pair from the\n      dictionary.\n\n      ``popitem()`` is useful to destructively iterate over a\n      dictionary, as often used in set algorithms.  If the dictionary\n      is empty, calling ``popitem()`` raises a ``KeyError``.\n\n   setdefault(key[, default])\n\n      If *key* is in the dictionary, return its value.  If not, insert\n      *key* with a value of *default* and return *default*.  *default*\n      defaults to ``None``.\n\n   update([other])\n\n      Update the dictionary with the key/value pairs from *other*,\n      overwriting existing keys.  Return ``None``.\n\n      ``update()`` accepts either another dictionary object or an\n      iterable of key/value pairs (as tuples or other iterables of\n      length two).  If keyword arguments are specified, the dictionary\n      is then updated with those key/value pairs: ``d.update(red=1,\n      blue=2)``.\n\n      Changed in version 2.4: Allowed the argument to be an iterable\n      of key/value pairs and allowed keyword arguments.\n\n   values()\n\n      Return a copy of the dictionary\'s list of values.  See the note\n      for ``dict.items()``.\n\n   viewitems()\n\n      Return a new view of the dictionary\'s items (``(key, value)``\n      pairs).  See below for documentation of view objects.\n\n      New in version 2.7.\n\n   viewkeys()\n\n      Return a new view of the dictionary\'s keys.  See below for\n      documentation of view objects.\n\n      New in version 2.7.\n\n   viewvalues()\n\n      Return a new view of the dictionary\'s values.  See below for\n      documentation of view objects.\n\n      New in version 2.7.\n\n\nDictionary view objects\n=======================\n\nThe objects returned by ``dict.viewkeys()``, ``dict.viewvalues()`` and\n``dict.viewitems()`` are *view objects*.  They provide a dynamic view\non the dictionary\'s entries, which means that when the dictionary\nchanges, the view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n   Return the number of entries in the dictionary.\n\niter(dictview)\n\n   Return an iterator over the keys, values or items (represented as\n   tuples of ``(key, value)``) in the dictionary.\n\n   Keys and values are iterated over in an arbitrary order which is\n   non-random, varies across Python implementations, and depends on\n   the dictionary\'s history of insertions and deletions. If keys,\n   values and items views are iterated over with no intervening\n   modifications to the dictionary, the order of items will directly\n   correspond.  This allows the creation of ``(value, key)`` pairs\n   using ``zip()``: ``pairs = zip(d.values(), d.keys())``.  Another\n   way to create the same list is ``pairs = [(v, k) for (k, v) in\n   d.items()]``.\n\n   Iterating views while adding or deleting entries in the dictionary\n   may raise a ``RuntimeError`` or fail to iterate over all entries.\n\nx in dictview\n\n   Return ``True`` if *x* is in the underlying dictionary\'s keys,\n   values or items (in the latter case, *x* should be a ``(key,\n   value)`` tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that (key, value) pairs are unique and\nhashable, then the items view is also set-like.  (Values views are not\ntreated as set-like since the entries are generally not unique.)  Then\nthese set operations are available ("other" refers either to another\nview or a set):\n\ndictview & other\n\n   Return the intersection of the dictview and the other object as a\n   new set.\n\ndictview | other\n\n   Return the union of the dictview and the other object as a new set.\n\ndictview - other\n\n   Return the difference between the dictview and the other object\n   (all elements in *dictview* that aren\'t in *other*) as a new set.\n\ndictview ^ other\n\n   Return the symmetric difference (all elements either in *dictview*\n   or *other*, but not in both) of the dictview and the other object\n   as a new set.\n\nAn example of dictionary view usage:\n\n   >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n   >>> keys = dishes.viewkeys()\n   >>> values = dishes.viewvalues()\n\n   >>> # iteration\n   >>> n = 0\n   >>> for val in values:\n   ...     n += val\n   >>> print(n)\n   504\n\n   >>> # keys and values are iterated over in the same order\n   >>> list(keys)\n   [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n   >>> list(values)\n   [2, 1, 1, 500]\n\n   >>> # view objects are dynamic and reflect dict changes\n   >>> del dishes[\'eggs\']\n   >>> del dishes[\'sausage\']\n   >>> list(keys)\n   [\'spam\', \'bacon\']\n\n   >>> # set operations\n   >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n   {\'bacon\'}\n',
  'typesmethods': '\nMethods\n*******\n\nMethods are functions that are called using the attribute notation.\nThere are two flavors: built-in methods (such as ``append()`` on\nlists) and class instance methods.  Built-in methods are described\nwith the types that support them.\n\nThe implementation adds two special read-only attributes to class\ninstance methods: ``m.im_self`` is the object on which the method\noperates, and ``m.im_func`` is the function implementing the method.\nCalling ``m(arg-1, arg-2, ..., arg-n)`` is completely equivalent to\ncalling ``m.im_func(m.im_self, arg-1, arg-2, ..., arg-n)``.\n\nClass instance methods are either *bound* or *unbound*, referring to\nwhether the method was accessed through an instance or a class,\nrespectively.  When a method is unbound, its ``im_self`` attribute\nwill be ``None`` and if called, an explicit ``self`` object must be\npassed as the first argument.  In this case, ``self`` must be an\ninstance of the unbound method\'s class (or a subclass of that class),\notherwise a ``TypeError`` is raised.\n\nLike function objects, methods objects support getting arbitrary\nattributes. However, since method attributes are actually stored on\nthe underlying function object (``meth.im_func``), setting method\nattributes on either bound or unbound methods is disallowed.\nAttempting to set an attribute on a method results in an\n``AttributeError`` being raised.  In order to set a method attribute,\nyou need to explicitly set it on the underlying function object:\n\n   >>> class C:\n   ...     def method(self):\n   ...         pass\n   ...\n   >>> c = C()\n   >>> c.method.whoami = \'my name is method\'  # can\'t set on the method\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   AttributeError: \'instancemethod\' object has no attribute \'whoami\'\n   >>> c.method.im_func.whoami = \'my name is method\'\n   >>> c.method.whoami\n   \'my name is method\'\n\nSee *The standard type hierarchy* for more information.\n',
  'typesmodules': "\nModules\n*******\n\nThe only special operation on a module is attribute access:\n``m.name``, where *m* is a module and *name* accesses a name defined\nin *m*'s symbol table. Module attributes can be assigned to.  (Note\nthat the ``import`` statement is not, strictly speaking, an operation\non a module object; ``import foo`` does not require a module object\nnamed *foo* to exist, rather it requires an (external) *definition*\nfor a module named *foo* somewhere.)\n\nA special attribute of every module is ``__dict__``. This is the\ndictionary containing the module's symbol table. Modifying this\ndictionary will actually change the module's symbol table, but direct\nassignment to the ``__dict__`` attribute is not possible (you can\nwrite ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but\nyou can't write ``m.__dict__ = {}``).  Modifying ``__dict__`` directly\nis not recommended.\n\nModules built into the interpreter are written like this: ``<module\n'sys' (built-in)>``.  If loaded from a file, they are written as\n``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.\n",
  'typesseq': '\nSequence Types --- ``str``, ``unicode``, ``list``, ``tuple``, ``bytearray``, ``buffer``, ``xrange``\n***************************************************************************************************\n\nThere are seven sequence types: strings, Unicode strings, lists,\ntuples, bytearrays, buffers, and xrange objects.\n\nFor other containers see the built in ``dict`` and ``set`` classes,\nand the ``collections`` module.\n\nString literals are written in single or double quotes: ``\'xyzzy\'``,\n``"frobozz"``.  See *String literals* for more about string literals.\nUnicode strings are much like strings, but are specified in the syntax\nusing a preceding ``\'u\'`` character: ``u\'abc\'``, ``u"def"``. In\naddition to the functionality described here, there are also string-\nspecific methods described in the *String Methods* section. Lists are\nconstructed with square brackets, separating items with commas: ``[a,\nb, c]``. Tuples are constructed by the comma operator (not within\nsquare brackets), with or without enclosing parentheses, but an empty\ntuple must have the enclosing parentheses, such as ``a, b, c`` or\n``()``.  A single item tuple must have a trailing comma, such as\n``(d,)``.\n\nBytearray objects are created with the built-in function\n``bytearray()``.\n\nBuffer objects are not directly supported by Python syntax, but can be\ncreated by calling the built-in function ``buffer()``.  They don\'t\nsupport concatenation or repetition.\n\nObjects of type xrange are similar to buffers in that there is no\nspecific syntax to create them, but they are created using the\n``xrange()`` function.  They don\'t support slicing, concatenation or\nrepetition, and using ``in``, ``not in``, ``min()`` or ``max()`` on\nthem is inefficient.\n\nMost sequence types support the following operations.  The ``in`` and\n``not in`` operations have the same priorities as the comparison\noperations.  The ``+`` and ``*`` operations have the same priority as\nthe corresponding numeric operations. [3] Additional methods are\nprovided for *Mutable Sequence Types*.\n\nThis table lists the sequence operations sorted in ascending priority\n(operations in the same box have the same priority).  In the table,\n*s* and *t* are sequences of the same type; *n*, *i* and *j* are\nintegers:\n\n+--------------------+----------------------------------+------------+\n| Operation          | Result                           | Notes      |\n+====================+==================================+============+\n| ``x in s``         | ``True`` if an item of *s* is    | (1)        |\n|                    | equal to *x*, else ``False``     |            |\n+--------------------+----------------------------------+------------+\n| ``x not in s``     | ``False`` if an item of *s* is   | (1)        |\n|                    | equal to *x*, else ``True``      |            |\n+--------------------+----------------------------------+------------+\n| ``s + t``          | the concatenation of *s* and *t* | (6)        |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s``   | *n* shallow copies of *s*        | (2)        |\n|                    | concatenated                     |            |\n+--------------------+----------------------------------+------------+\n| ``s[i]``           | *i*th item of *s*, origin 0      | (3)        |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]``         | slice of *s* from *i* to *j*     | (3)(4)     |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]``       | slice of *s* from *i* to *j*     | (3)(5)     |\n|                    | with step *k*                    |            |\n+--------------------+----------------------------------+------------+\n| ``len(s)``         | length of *s*                    |            |\n+--------------------+----------------------------------+------------+\n| ``min(s)``         | smallest item of *s*             |            |\n+--------------------+----------------------------------+------------+\n| ``max(s)``         | largest item of *s*              |            |\n+--------------------+----------------------------------+------------+\n| ``s.index(x)``     | index of the first occurrence of |            |\n|                    | *x* in *s*                       |            |\n+--------------------+----------------------------------+------------+\n| ``s.count(x)``     | total number of occurrences of   |            |\n|                    | *x* in *s*                       |            |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular, tuples and\nlists are compared lexicographically by comparing corresponding\nelements. This means that to compare equal, every element must compare\nequal and the two sequences must be of the same type and have the same\nlength. (For full details see *Comparisons* in the language\nreference.)\n\nNotes:\n\n1. When *s* is a string or Unicode string object the ``in`` and ``not\n   in`` operations act like a substring test.  In Python versions\n   before 2.3, *x* had to be a string of length 1. In Python 2.3 and\n   beyond, *x* may be a string of any length.\n\n2. Values of *n* less than ``0`` are treated as ``0`` (which yields an\n   empty sequence of the same type as *s*).  Note also that the copies\n   are shallow; nested structures are not copied.  This often haunts\n   new Python programmers; consider:\n\n   >>> lists = [[]] * 3\n   >>> lists\n   [[], [], []]\n   >>> lists[0].append(3)\n   >>> lists\n   [[3], [3], [3]]\n\n   What has happened is that ``[[]]`` is a one-element list containing\n   an empty list, so all three elements of ``[[]] * 3`` are (pointers\n   to) this single empty list.  Modifying any of the elements of\n   ``lists`` modifies this single list. You can create a list of\n   different lists this way:\n\n   >>> lists = [[] for i in range(3)]\n   >>> lists[0].append(3)\n   >>> lists[1].append(5)\n   >>> lists[2].append(7)\n   >>> lists\n   [[3], [5], [7]]\n\n3. If *i* or *j* is negative, the index is relative to the end of the\n   string: ``len(s) + i`` or ``len(s) + j`` is substituted.  But note\n   that ``-0`` is still ``0``.\n\n4. The slice of *s* from *i* to *j* is defined as the sequence of\n   items with index *k* such that ``i <= k < j``.  If *i* or *j* is\n   greater than ``len(s)``, use ``len(s)``.  If *i* is omitted or\n   ``None``, use ``0``.  If *j* is omitted or ``None``, use\n   ``len(s)``.  If *i* is greater than or equal to *j*, the slice is\n   empty.\n\n5. The slice of *s* from *i* to *j* with step *k* is defined as the\n   sequence of items with index  ``x = i + n*k`` such that ``0 <= n <\n   (j-i)/k``.  In other words, the indices are ``i``, ``i+k``,\n   ``i+2*k``, ``i+3*k`` and so on, stopping when *j* is reached (but\n   never including *j*).  If *i* or *j* is greater than ``len(s)``,\n   use ``len(s)``.  If *i* or *j* are omitted or ``None``, they become\n   "end" values (which end depends on the sign of *k*).  Note, *k*\n   cannot be zero. If *k* is ``None``, it is treated like ``1``.\n\n6. **CPython implementation detail:** If *s* and *t* are both strings,\n   some Python implementations such as CPython can usually perform an\n   in-place optimization for assignments of the form ``s = s + t`` or\n   ``s += t``.  When applicable, this optimization makes quadratic\n   run-time much less likely.  This optimization is both version and\n   implementation dependent.  For performance sensitive code, it is\n   preferable to use the ``str.join()`` method which assures\n   consistent linear concatenation performance across versions and\n   implementations.\n\n   Changed in version 2.4: Formerly, string concatenation never\n   occurred in-place.\n\n\nString Methods\n==============\n\nBelow are listed the string methods which both 8-bit strings and\nUnicode objects support.  Some of them are also available on\n``bytearray`` objects.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, unicode, list, tuple,\nbytearray, buffer, xrange* section. To output formatted strings use\ntemplate strings or the ``%`` operator described in the *String\nFormatting Operations* section. Also, see the ``re`` module for string\nfunctions based on regular expressions.\n\nstr.capitalize()\n\n   Return a copy of the string with its first character capitalized\n   and the rest lowercased.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.center(width[, fillchar])\n\n   Return centered in a string of length *width*. Padding is done\n   using the specified *fillchar* (default is a space).\n\n   Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.count(sub[, start[, end]])\n\n   Return the number of non-overlapping occurrences of substring *sub*\n   in the range [*start*, *end*].  Optional arguments *start* and\n   *end* are interpreted as in slice notation.\n\nstr.decode([encoding[, errors]])\n\n   Decodes the string using the codec registered for *encoding*.\n   *encoding* defaults to the default string encoding.  *errors* may\n   be given to set a different error handling scheme.  The default is\n   ``\'strict\'``, meaning that encoding errors raise ``UnicodeError``.\n   Other possible values are ``\'ignore\'``, ``\'replace\'`` and any other\n   name registered via ``codecs.register_error()``, see section *Codec\n   Base Classes*.\n\n   New in version 2.2.\n\n   Changed in version 2.3: Support for other error handling schemes\n   added.\n\n   Changed in version 2.7: Support for keyword arguments added.\n\nstr.encode([encoding[, errors]])\n\n   Return an encoded version of the string.  Default encoding is the\n   current default string encoding.  *errors* may be given to set a\n   different error handling scheme.  The default for *errors* is\n   ``\'strict\'``, meaning that encoding errors raise a\n   ``UnicodeError``.  Other possible values are ``\'ignore\'``,\n   ``\'replace\'``, ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and\n   any other name registered via ``codecs.register_error()``, see\n   section *Codec Base Classes*. For a list of possible encodings, see\n   section *Standard Encodings*.\n\n   New in version 2.0.\n\n   Changed in version 2.3: Support for ``\'xmlcharrefreplace\'`` and\n   ``\'backslashreplace\'`` and other error handling schemes added.\n\n   Changed in version 2.7: Support for keyword arguments added.\n\nstr.endswith(suffix[, start[, end]])\n\n   Return ``True`` if the string ends with the specified *suffix*,\n   otherwise return ``False``.  *suffix* can also be a tuple of\n   suffixes to look for.  With optional *start*, test beginning at\n   that position.  With optional *end*, stop comparing at that\n   position.\n\n   Changed in version 2.5: Accept tuples as *suffix*.\n\nstr.expandtabs([tabsize])\n\n   Return a copy of the string where all tab characters are replaced\n   by one or more spaces, depending on the current column and the\n   given tab size.  Tab positions occur every *tabsize* characters\n   (default is 8, giving tab positions at columns 0, 8, 16 and so on).\n   To expand the string, the current column is set to zero and the\n   string is examined character by character.  If the character is a\n   tab (``\\t``), one or more space characters are inserted in the\n   result until the current column is equal to the next tab position.\n   (The tab character itself is not copied.)  If the character is a\n   newline (``\\n``) or return (``\\r``), it is copied and the current\n   column is reset to zero.  Any other character is copied unchanged\n   and the current column is incremented by one regardless of how the\n   character is represented when printed.\n\n   >>> \'01\\t012\\t0123\\t01234\'.expandtabs()\n   \'01      012     0123    01234\'\n   >>> \'01\\t012\\t0123\\t01234\'.expandtabs(4)\n   \'01  012 0123    01234\'\n\nstr.find(sub[, start[, end]])\n\n   Return the lowest index in the string where substring *sub* is\n   found, such that *sub* is contained in the slice ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` if *sub* is not found.\n\n   Note: The ``find()`` method should be used only if you need to know the\n     position of *sub*.  To check if *sub* is a substring or not, use\n     the ``in`` operator:\n\n        >>> \'Py\' in \'Python\'\n        True\n\nstr.format(*args, **kwargs)\n\n   Perform a string formatting operation.  The string on which this\n   method is called can contain literal text or replacement fields\n   delimited by braces ``{}``.  Each replacement field contains either\n   the numeric index of a positional argument, or the name of a\n   keyword argument.  Returns a copy of the string where each\n   replacement field is replaced with the string value of the\n   corresponding argument.\n\n   >>> "The sum of 1 + 2 is {0}".format(1+2)\n   \'The sum of 1 + 2 is 3\'\n\n   See *Format String Syntax* for a description of the various\n   formatting options that can be specified in format strings.\n\n   This method of string formatting is the new standard in Python 3,\n   and should be preferred to the ``%`` formatting described in\n   *String Formatting Operations* in new code.\n\n   New in version 2.6.\n\nstr.index(sub[, start[, end]])\n\n   Like ``find()``, but raise ``ValueError`` when the substring is not\n   found.\n\nstr.isalnum()\n\n   Return true if all characters in the string are alphanumeric and\n   there is at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isalpha()\n\n   Return true if all characters in the string are alphabetic and\n   there is at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isdigit()\n\n   Return true if all characters in the string are digits and there is\n   at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.islower()\n\n   Return true if all cased characters [4] in the string are lowercase\n   and there is at least one cased character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isspace()\n\n   Return true if there are only whitespace characters in the string\n   and there is at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.istitle()\n\n   Return true if the string is a titlecased string and there is at\n   least one character, for example uppercase characters may only\n   follow uncased characters and lowercase characters only cased ones.\n   Return false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isupper()\n\n   Return true if all cased characters [4] in the string are uppercase\n   and there is at least one cased character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.join(iterable)\n\n   Return a string which is the concatenation of the strings in the\n   *iterable* *iterable*.  The separator between elements is the\n   string providing this method.\n\nstr.ljust(width[, fillchar])\n\n   Return the string left justified in a string of length *width*.\n   Padding is done using the specified *fillchar* (default is a\n   space).  The original string is returned if *width* is less than or\n   equal to ``len(s)``.\n\n   Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.lower()\n\n   Return a copy of the string with all the cased characters [4]\n   converted to lowercase.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.lstrip([chars])\n\n   Return a copy of the string with leading characters removed.  The\n   *chars* argument is a string specifying the set of characters to be\n   removed.  If omitted or ``None``, the *chars* argument defaults to\n   removing whitespace.  The *chars* argument is not a prefix; rather,\n   all combinations of its values are stripped:\n\n   >>> \'   spacious   \'.lstrip()\n   \'spacious   \'\n   >>> \'www.example.com\'.lstrip(\'cmowz.\')\n   \'example.com\'\n\n   Changed in version 2.2.2: Support for the *chars* argument.\n\nstr.partition(sep)\n\n   Split the string at the first occurrence of *sep*, and return a\n   3-tuple containing the part before the separator, the separator\n   itself, and the part after the separator.  If the separator is not\n   found, return a 3-tuple containing the string itself, followed by\n   two empty strings.\n\n   New in version 2.5.\n\nstr.replace(old, new[, count])\n\n   Return a copy of the string with all occurrences of substring *old*\n   replaced by *new*.  If the optional argument *count* is given, only\n   the first *count* occurrences are replaced.\n\nstr.rfind(sub[, start[, end]])\n\n   Return the highest index in the string where substring *sub* is\n   found, such that *sub* is contained within ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n   Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n   is not found.\n\nstr.rjust(width[, fillchar])\n\n   Return the string right justified in a string of length *width*.\n   Padding is done using the specified *fillchar* (default is a\n   space). The original string is returned if *width* is less than or\n   equal to ``len(s)``.\n\n   Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.rpartition(sep)\n\n   Split the string at the last occurrence of *sep*, and return a\n   3-tuple containing the part before the separator, the separator\n   itself, and the part after the separator.  If the separator is not\n   found, return a 3-tuple containing two empty strings, followed by\n   the string itself.\n\n   New in version 2.5.\n\nstr.rsplit([sep[, maxsplit]])\n\n   Return a list of the words in the string, using *sep* as the\n   delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n   are done, the *rightmost* ones.  If *sep* is not specified or\n   ``None``, any whitespace string is a separator.  Except for\n   splitting from the right, ``rsplit()`` behaves like ``split()``\n   which is described in detail below.\n\n   New in version 2.4.\n\nstr.rstrip([chars])\n\n   Return a copy of the string with trailing characters removed.  The\n   *chars* argument is a string specifying the set of characters to be\n   removed.  If omitted or ``None``, the *chars* argument defaults to\n   removing whitespace.  The *chars* argument is not a suffix; rather,\n   all combinations of its values are stripped:\n\n   >>> \'   spacious   \'.rstrip()\n   \'   spacious\'\n   >>> \'mississippi\'.rstrip(\'ipz\')\n   \'mississ\'\n\n   Changed in version 2.2.2: Support for the *chars* argument.\n\nstr.split([sep[, maxsplit]])\n\n   Return a list of the words in the string, using *sep* as the\n   delimiter string.  If *maxsplit* is given, at most *maxsplit*\n   splits are done (thus, the list will have at most ``maxsplit+1``\n   elements).  If *maxsplit* is not specified or ``-1``, then there is\n   no limit on the number of splits (all possible splits are made).\n\n   If *sep* is given, consecutive delimiters are not grouped together\n   and are deemed to delimit empty strings (for example,\n   ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``).  The *sep*\n   argument may consist of multiple characters (for example,\n   ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n   an empty string with a specified separator returns ``[\'\']``.\n\n   If *sep* is not specified or is ``None``, a different splitting\n   algorithm is applied: runs of consecutive whitespace are regarded\n   as a single separator, and the result will contain no empty strings\n   at the start or end if the string has leading or trailing\n   whitespace.  Consequently, splitting an empty string or a string\n   consisting of just whitespace with a ``None`` separator returns\n   ``[]``.\n\n   For example, ``\' 1  2   3  \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n   and ``\'  1  2   3  \'.split(None, 1)`` returns ``[\'1\', \'2   3  \']``.\n\nstr.splitlines([keepends])\n\n   Return a list of the lines in the string, breaking at line\n   boundaries. This method uses the *universal newlines* approach to\n   splitting lines. Line breaks are not included in the resulting list\n   unless *keepends* is given and true.\n\n   For example, ``\'ab c\\n\\nde fg\\rkl\\r\\n\'.splitlines()`` returns\n   ``[\'ab c\', \'\', \'de fg\', \'kl\']``, while the same call with\n   ``splitlines(True)`` returns ``[\'ab c\\n\', \'\\n\', \'de fg\\r\',\n   \'kl\\r\\n\']``.\n\n   Unlike ``split()`` when a delimiter string *sep* is given, this\n   method returns an empty list for the empty string, and a terminal\n   line break does not result in an extra line.\n\nstr.startswith(prefix[, start[, end]])\n\n   Return ``True`` if string starts with the *prefix*, otherwise\n   return ``False``. *prefix* can also be a tuple of prefixes to look\n   for.  With optional *start*, test string beginning at that\n   position.  With optional *end*, stop comparing string at that\n   position.\n\n   Changed in version 2.5: Accept tuples as *prefix*.\n\nstr.strip([chars])\n\n   Return a copy of the string with the leading and trailing\n   characters removed. The *chars* argument is a string specifying the\n   set of characters to be removed. If omitted or ``None``, the\n   *chars* argument defaults to removing whitespace. The *chars*\n   argument is not a prefix or suffix; rather, all combinations of its\n   values are stripped:\n\n   >>> \'   spacious   \'.strip()\n   \'spacious\'\n   >>> \'www.example.com\'.strip(\'cmowz.\')\n   \'example\'\n\n   Changed in version 2.2.2: Support for the *chars* argument.\n\nstr.swapcase()\n\n   Return a copy of the string with uppercase characters converted to\n   lowercase and vice versa.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.title()\n\n   Return a titlecased version of the string where words start with an\n   uppercase character and the remaining characters are lowercase.\n\n   The algorithm uses a simple language-independent definition of a\n   word as groups of consecutive letters.  The definition works in\n   many contexts but it means that apostrophes in contractions and\n   possessives form word boundaries, which may not be the desired\n   result:\n\n      >>> "they\'re bill\'s friends from the UK".title()\n      "They\'Re Bill\'S Friends From The Uk"\n\n   A workaround for apostrophes can be constructed using regular\n   expressions:\n\n      >>> import re\n      >>> def titlecase(s):\n      ...     return re.sub(r"[A-Za-z]+(\'[A-Za-z]+)?",\n      ...                   lambda mo: mo.group(0)[0].upper() +\n      ...                              mo.group(0)[1:].lower(),\n      ...                   s)\n      ...\n      >>> titlecase("they\'re bill\'s friends.")\n      "They\'re Bill\'s Friends."\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.translate(table[, deletechars])\n\n   Return a copy of the string where all characters occurring in the\n   optional argument *deletechars* are removed, and the remaining\n   characters have been mapped through the given translation table,\n   which must be a string of length 256.\n\n   You can use the ``maketrans()`` helper function in the ``string``\n   module to create a translation table. For string objects, set the\n   *table* argument to ``None`` for translations that only delete\n   characters:\n\n   >>> \'read this short text\'.translate(None, \'aeiou\')\n   \'rd ths shrt txt\'\n\n   New in version 2.6: Support for a ``None`` *table* argument.\n\n   For Unicode objects, the ``translate()`` method does not accept the\n   optional *deletechars* argument.  Instead, it returns a copy of the\n   *s* where all characters have been mapped through the given\n   translation table which must be a mapping of Unicode ordinals to\n   Unicode ordinals, Unicode strings or ``None``. Unmapped characters\n   are left untouched. Characters mapped to ``None`` are deleted.\n   Note, a more flexible approach is to create a custom character\n   mapping codec using the ``codecs`` module (see ``encodings.cp1251``\n   for an example).\n\nstr.upper()\n\n   Return a copy of the string with all the cased characters [4]\n   converted to uppercase.  Note that ``str.upper().isupper()`` might\n   be ``False`` if ``s`` contains uncased characters or if the Unicode\n   category of the resulting character(s) is not "Lu" (Letter,\n   uppercase), but e.g. "Lt" (Letter, titlecase).\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.zfill(width)\n\n   Return the numeric string left filled with zeros in a string of\n   length *width*.  A sign prefix is handled correctly.  The original\n   string is returned if *width* is less than or equal to ``len(s)``.\n\n   New in version 2.2.2.\n\nThe following methods are present only on unicode objects:\n\nunicode.isnumeric()\n\n   Return ``True`` if there are only numeric characters in S,\n   ``False`` otherwise. Numeric characters include digit characters,\n   and all characters that have the Unicode numeric value property,\n   e.g. U+2155, VULGAR FRACTION ONE FIFTH.\n\nunicode.isdecimal()\n\n   Return ``True`` if there are only decimal characters in S,\n   ``False`` otherwise. Decimal characters include digit characters,\n   and all characters that can be used to form decimal-radix numbers,\n   e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\n\n\nString Formatting Operations\n============================\n\nString and Unicode objects have one unique built-in operation: the\n``%`` operator (modulo).  This is also known as the string\n*formatting* or *interpolation* operator.  Given ``format % values``\n(where *format* is a string or Unicode object), ``%`` conversion\nspecifications in *format* are replaced with zero or more elements of\n*values*.  The effect is similar to the using ``sprintf()`` in the C\nlanguage.  If *format* is a Unicode object, or if any of the objects\nbeing converted using the ``%s`` conversion are Unicode objects, the\nresult will also be a Unicode object.\n\nIf *format* requires a single argument, *values* may be a single non-\ntuple object. [5]  Otherwise, *values* must be a tuple with exactly\nthe number of items specified by the format string, or a single\nmapping object (for example, a dictionary).\n\nA conversion specifier contains two or more characters and has the\nfollowing components, which must occur in this order:\n\n1. The ``\'%\'`` character, which marks the start of the specifier.\n\n2. Mapping key (optional), consisting of a parenthesised sequence of\n   characters (for example, ``(somename)``).\n\n3. Conversion flags (optional), which affect the result of some\n   conversion types.\n\n4. Minimum field width (optional).  If specified as an ``\'*\'``\n   (asterisk), the actual width is read from the next element of the\n   tuple in *values*, and the object to convert comes after the\n   minimum field width and optional precision.\n\n5. Precision (optional), given as a ``\'.\'`` (dot) followed by the\n   precision.  If specified as ``\'*\'`` (an asterisk), the actual width\n   is read from the next element of the tuple in *values*, and the\n   value to convert comes after the precision.\n\n6. Length modifier (optional).\n\n7. Conversion type.\n\nWhen the right argument is a dictionary (or other mapping type), then\nthe formats in the string *must* include a parenthesised mapping key\ninto that dictionary inserted immediately after the ``\'%\'`` character.\nThe mapping key selects the value to be formatted from the mapping.\nFor example:\n\n>>> print \'%(language)s has %(number)03d quote types.\' % \\\n...       {"language": "Python", "number": 2}\nPython has 002 quote types.\n\nIn this case no ``*`` specifiers may occur in a format (since they\nrequire a sequential parameter list).\n\nThe conversion flag characters are:\n\n+-----------+-----------------------------------------------------------------------+\n| Flag      | Meaning                                                               |\n+===========+=======================================================================+\n| ``\'#\'``   | The value conversion will use the "alternate form" (where defined     |\n|           | below).                                                               |\n+-----------+-----------------------------------------------------------------------+\n| ``\'0\'``   | The conversion will be zero padded for numeric values.                |\n+-----------+-----------------------------------------------------------------------+\n| ``\'-\'``   | The converted value is left adjusted (overrides the ``\'0\'``           |\n|           | conversion if both are given).                                        |\n+-----------+-----------------------------------------------------------------------+\n| ``\' \'``   | (a space) A blank should be left before a positive number (or empty   |\n|           | string) produced by a signed conversion.                              |\n+-----------+-----------------------------------------------------------------------+\n| ``\'+\'``   | A sign character (``\'+\'`` or ``\'-\'``) will precede the conversion     |\n|           | (overrides a "space" flag).                                           |\n+-----------+-----------------------------------------------------------------------+\n\nA length modifier (``h``, ``l``, or ``L``) may be present, but is\nignored as it is not necessary for Python -- so e.g. ``%ld`` is\nidentical to ``%d``.\n\nThe conversion types are:\n\n+--------------+-------------------------------------------------------+---------+\n| Conversion   | Meaning                                               | Notes   |\n+==============+=======================================================+=========+\n| ``\'d\'``      | Signed integer decimal.                               |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'i\'``      | Signed integer decimal.                               |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'o\'``      | Signed octal value.                                   | (1)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'u\'``      | Obsolete type -- it is identical to ``\'d\'``.          | (7)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'x\'``      | Signed hexadecimal (lowercase).                       | (2)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'X\'``      | Signed hexadecimal (uppercase).                       | (2)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'e\'``      | Floating point exponential format (lowercase).        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'E\'``      | Floating point exponential format (uppercase).        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'f\'``      | Floating point decimal format.                        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'F\'``      | Floating point decimal format.                        | (3)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'g\'``      | Floating point format. Uses lowercase exponential     | (4)     |\n|              | format if exponent is less than -4 or not less than   |         |\n|              | precision, decimal format otherwise.                  |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'G\'``      | Floating point format. Uses uppercase exponential     | (4)     |\n|              | format if exponent is less than -4 or not less than   |         |\n|              | precision, decimal format otherwise.                  |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'c\'``      | Single character (accepts integer or single character |         |\n|              | string).                                              |         |\n+--------------+-------------------------------------------------------+---------+\n| ``\'r\'``      | String (converts any Python object using *repr()*).   | (5)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'s\'``      | String (converts any Python object using ``str()``).  | (6)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'%\'``      | No argument is converted, results in a ``\'%\'``        |         |\n|              | character in the result.                              |         |\n+--------------+-------------------------------------------------------+---------+\n\nNotes:\n\n1. The alternate form causes a leading zero (``\'0\'``) to be inserted\n   between left-hand padding and the formatting of the number if the\n   leading character of the result is not already a zero.\n\n2. The alternate form causes a leading ``\'0x\'`` or ``\'0X\'`` (depending\n   on whether the ``\'x\'`` or ``\'X\'`` format was used) to be inserted\n   between left-hand padding and the formatting of the number if the\n   leading character of the result is not already a zero.\n\n3. The alternate form causes the result to always contain a decimal\n   point, even if no digits follow it.\n\n   The precision determines the number of digits after the decimal\n   point and defaults to 6.\n\n4. The alternate form causes the result to always contain a decimal\n   point, and trailing zeroes are not removed as they would otherwise\n   be.\n\n   The precision determines the number of significant digits before\n   and after the decimal point and defaults to 6.\n\n5. The ``%r`` conversion was added in Python 2.0.\n\n   The precision determines the maximal number of characters used.\n\n6. If the object or format provided is a ``unicode`` string, the\n   resulting string will also be ``unicode``.\n\n   The precision determines the maximal number of characters used.\n\n7. See **PEP 237**.\n\nSince Python strings have an explicit length, ``%s`` conversions do\nnot assume that ``\'\\0\'`` is the end of the string.\n\nChanged in version 2.7: ``%f`` conversions for numbers whose absolute\nvalue is over 1e50 are no longer replaced by ``%g`` conversions.\n\nAdditional string operations are defined in standard modules\n``string`` and ``re``.\n\n\nXRange Type\n===========\n\nThe ``xrange`` type is an immutable sequence which is commonly used\nfor looping.  The advantage of the ``xrange`` type is that an\n``xrange`` object will always take the same amount of memory, no\nmatter the size of the range it represents.  There are no consistent\nperformance advantages.\n\nXRange objects have very little behavior: they only support indexing,\niteration, and the ``len()`` function.\n\n\nMutable Sequence Types\n======================\n\nList and ``bytearray`` objects support additional operations that\nallow in-place modification of the object. Other mutable sequence\ntypes (when added to the language) should also support these\noperations. Strings and tuples are immutable sequence types: such\nobjects cannot be modified once created. The following operations are\ndefined on mutable sequence types (where *x* is an arbitrary object):\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation                      | Result                           | Notes                 |\n+================================+==================================+=======================+\n| ``s[i] = x``                   | item *i* of *s* is replaced by   |                       |\n|                                | *x*                              |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t``                 | slice of *s* from *i* to *j* is  |                       |\n|                                | replaced by the contents of the  |                       |\n|                                | iterable *t*                     |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]``                 | same as ``s[i:j] = []``          |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t``               | the elements of ``s[i:j:k]`` are | (1)                   |\n|                                | replaced by those of *t*         |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]``               | removes the elements of          |                       |\n|                                | ``s[i:j:k]`` from the list       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)``                | same as ``s[len(s):len(s)] =     | (2)                   |\n|                                | [x]``                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (3)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)``                 | return number of *i*\'s for which |                       |\n|                                | ``s[i] == x``                    |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])``       | return smallest *k* such that    | (4)                   |\n|                                | ``s[k] == x`` and ``i <= k < j`` |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (5)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (6)                   |\n|                                | return x``                       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (4)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()``                | reverses the items of *s* in     | (7)                   |\n|                                | place                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([cmp[, key[,          | sort the items of *s* in place   | (7)(8)(9)(10)         |\n| reverse]]])``                  |                                  |                       |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is  replacing.\n\n2. The C implementation of Python has historically accepted multiple\n   parameters and implicitly joined them into a tuple; this no longer\n   works in Python 2.0.  Use of this misfeature has been deprecated\n   since Python 1.4.\n\n3. *x* can be any iterable object.\n\n4. Raises ``ValueError`` when *x* is not found in *s*. When a negative\n   index is passed as the second or third parameter to the ``index()``\n   method, the list length is added, as for slice indices.  If it is\n   still negative, it is truncated to zero, as for slice indices.\n\n   Changed in version 2.3: Previously, ``index()`` didn\'t have\n   arguments for specifying start and stop positions.\n\n5. When a negative index is passed as the first parameter to the\n   ``insert()`` method, the list length is added, as for slice\n   indices.  If it is still negative, it is truncated to zero, as for\n   slice indices.\n\n   Changed in version 2.3: Previously, all negative indices were\n   truncated to zero.\n\n6. The ``pop()`` method\'s optional argument *i* defaults to ``-1``, so\n   that by default the last item is removed and returned.\n\n7. The ``sort()`` and ``reverse()`` methods modify the list in place\n   for economy of space when sorting or reversing a large list.  To\n   remind you that they operate by side effect, they don\'t return the\n   sorted or reversed list.\n\n8. The ``sort()`` method takes optional arguments for controlling the\n   comparisons.\n\n   *cmp* specifies a custom comparison function of two arguments (list\n   items) which should return a negative, zero or positive number\n   depending on whether the first argument is considered smaller than,\n   equal to, or larger than the second argument: ``cmp=lambda x,y:\n   cmp(x.lower(), y.lower())``.  The default value is ``None``.\n\n   *key* specifies a function of one argument that is used to extract\n   a comparison key from each list element: ``key=str.lower``.  The\n   default value is ``None``.\n\n   *reverse* is a boolean value.  If set to ``True``, then the list\n   elements are sorted as if each comparison were reversed.\n\n   In general, the *key* and *reverse* conversion processes are much\n   faster than specifying an equivalent *cmp* function.  This is\n   because *cmp* is called multiple times for each list element while\n   *key* and *reverse* touch each element only once.  Use\n   ``functools.cmp_to_key()`` to convert an old-style *cmp* function\n   to a *key* function.\n\n   Changed in version 2.3: Support for ``None`` as an equivalent to\n   omitting *cmp* was added.\n\n   Changed in version 2.4: Support for *key* and *reverse* was added.\n\n9. Starting with Python 2.3, the ``sort()`` method is guaranteed to be\n   stable.  A sort is stable if it guarantees not to change the\n   relative order of elements that compare equal --- this is helpful\n   for sorting in multiple passes (for example, sort by department,\n   then by salary grade).\n\n10. **CPython implementation detail:** While a list is being sorted,\n    the effect of attempting to mutate, or even inspect, the list is\n    undefined.  The C implementation of Python 2.3 and newer makes the\n    list appear empty for the duration, and raises ``ValueError`` if\n    it can detect that the list has been mutated during a sort.\n',