Fix markup errors and update pydoc topics.

1 files changed, 7 insertions, 7 deletions

diff --git a/Lib/pydoc_data/topics.py b/Lib/pydoc_data/topics.py
index 55e3121..2bcf33a 100644
--- a/Lib/pydoc_data/topics.py
+++ b/Lib/pydoc_data/topics.py
@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# Autogenerated by Sphinx on Tue Jun 26 09:10:52 2012
+# Autogenerated by Sphinx on Sat Aug 11 08:41:05 2012
 topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAssert statements are a convenient way to insert debugging assertions\ninto a program:\n\n   assert_stmt ::= "assert" expression ["," expression]\n\nThe simple form, ``assert expression``, is equivalent to\n\n   if __debug__:\n      if not expression: raise AssertionError\n\nThe extended form, ``assert expression1, expression2``, is equivalent\nto\n\n   if __debug__:\n      if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that ``__debug__`` and ``AssertionError``\nrefer to the built-in variables with those names.  In the current\nimplementation, the built-in variable ``__debug__`` is ``True`` under\nnormal circumstances, ``False`` when optimization is requested\n(command line option -O).  The current code generator emits no code\nfor an assert statement when optimization is requested at compile\ntime.  Note that it is unnecessary to include the source code for the\nexpression that failed in the error message; it will be displayed as\npart of the stack trace.\n\nAssignments to ``__debug__`` are illegal.  The value for the built-in\nvariable is determined when the interpreter starts.\n',
  'assignment': '\nAssignment statements\n*********************\n\nAssignment statements are used to (re)bind names to values and to\nmodify attributes or items of mutable objects:\n\n   assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)\n   target_list     ::= target ("," target)* [","]\n   target          ::= identifier\n              | "(" target_list ")"\n              | "[" target_list "]"\n              | attributeref\n              | subscription\n              | slicing\n              | "*" target\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable.  The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list, optionally enclosed in\nparentheses or square brackets, is recursively defined as follows.\n\n* If the target list is a single target: The object is assigned to\n  that target.\n\n* If the target list is a comma-separated list of targets: 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\n  * If the target list contains one target prefixed with an asterisk,\n    called a "starred" target: The object must be a sequence with at\n    least as many items as there are targets in the target list, minus\n    one.  The first items of the sequence are assigned, from left to\n    right, to the targets before the starred target.  The final items\n    of the sequence are assigned to the targets after the starred\n    target.  A list of the remaining items in the sequence is then\n    assigned to the starred target (the list can be empty).\n\n  * Else: The object must be a sequence with the same number of items\n    as there are targets in the target list, and the items are\n    assigned, from left to right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n  * If the name does not occur in a ``global`` or ``nonlocal``\n    statement in the current code block: the name is bound to the\n    object in the current local namespace.\n\n  * Otherwise: the name is bound to the object in the global namespace\n    or the outer namespace determined by ``nonlocal``, respectively.\n\n  The name is rebound if it was already bound.  This may cause the\n  reference count for the object previously bound to the name to reach\n  zero, causing the object to be deallocated and its destructor (if it\n  has one) to be called.\n\n* 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 an integer.  If it is negative, the sequence\'s\n  length is added to it.  The resulting value must be a nonnegative\n  integer less than the sequence\'s length, and the sequence is asked\n  to assign the assigned object to its item with that index.  If the\n  index is out of range, ``IndexError`` is raised (assignment to a\n  subscripted sequence cannot add new items to a list).\n\n  If the primary is a mapping object (such as a dictionary), the\n  subscript must have a type compatible with the mapping\'s key type,\n  and the mapping is then asked to create a key/datum pair which maps\n  the subscript to the assigned object.  This can either replace an\n  existing key/value pair with the same key value, or insert a new\n  key/value pair (if no key with the same value existed).\n\n  For user-defined objects, the ``__setitem__()`` method is called\n  with appropriate arguments.\n\n* If the target is a slicing: The primary expression in the reference\n  is evaluated.  It should yield a mutable sequence object (such as a\n  list).  The assigned object should be a sequence object of the same\n  type.  Next, the lower and upper bound expressions are evaluated,\n  insofar they are present; defaults are zero and the sequence\'s\n  length.  The bounds should evaluate to integers. If either bound is\n  negative, the sequence\'s length is added to it.  The resulting\n  bounds are clipped to lie between zero and the sequence\'s length,\n  inclusive.  Finally, the sequence object is asked to replace the\n  slice with the items of the assigned sequence.  The length of the\n  slice may be different from the length of the assigned sequence,\n  thus changing the length of the target sequence, if the object\n  allows it.\n\n**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\nSee also:\n\n   **PEP 3132** - Extended Iterable Unpacking\n      The specification for the ``*target`` feature.\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n   augmented_assignment_stmt ::= 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 in front of the name, with leading underscores removed, and\na single underscore inserted in front of the class name.  For example,\nthe identifier ``__spam`` occurring in a class named ``Ham`` will be\ntransformed to ``_Ham__spam``.  This transformation is independent of\nthe syntactical context in which the identifier is used.  If the\ntransformed name is extremely long (longer than 255 characters),\nimplementation defined truncation may happen.  If the class name\nconsists only of underscores, no transformation is done.\n',
@@ -23,7 +23,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss
  'context-managers': '\nWith Statement Context Managers\n*******************************\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code.  Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n   Enter the runtime context related to this object. The ``with``\n   statement will bind this method\'s return value to the target(s)\n   specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n   Exit the runtime context related to this object. The parameters\n   describe the exception that caused the context to be exited. If the\n   context was exited without an exception, all three arguments will\n   be ``None``.\n\n   If an exception is supplied, and the method wishes to suppress the\n   exception (i.e., prevent it from being propagated), it should\n   return a true value. Otherwise, the exception will be processed\n   normally upon exit from this method.\n\n   Note that ``__exit__()`` methods should not reraise the passed-in\n   exception; this is the caller\'s responsibility.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n',
  'continue': '\nThe ``continue`` statement\n**************************\n\n   continue_stmt ::= "continue"\n\n``continue`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition or\n``finally`` clause within that loop.  It continues with the next cycle\nof the nearest enclosing loop.\n\nWhen ``continue`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nstarting the next loop cycle.\n',
  'conversions': '\nArithmetic conversions\n**********************\n\nWhen a description of an arithmetic operator below uses the phrase\n"the numeric arguments are converted to a common type," this means\nthat the operator implementation for built-in types works that way:\n\n* If either argument is a complex number, the other is converted to\n  complex;\n\n* otherwise, if either argument is a floating point number, the other\n  is converted to floating point;\n\n* otherwise, both must be integers and no conversion is necessary.\n\nSome additional rules apply for certain operators (e.g., a string left\nargument to the \'%\' operator).  Extensions must define their own\nconversion behavior.\n',
- 'customization': '\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n   Called to create a new instance of class *cls*.  ``__new__()`` is a\n   static method (special-cased so you need not declare it as such)\n   that takes the class of which an instance was requested as its\n   first argument.  The remaining arguments are those passed to the\n   object constructor expression (the call to the class).  The return\n   value of ``__new__()`` should be the new object instance (usually\n   an instance of *cls*).\n\n   Typical implementations create a new instance of the class by\n   invoking the superclass\'s ``__new__()`` method using\n   ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n   arguments and then modifying the newly-created instance as\n   necessary before returning it.\n\n   If ``__new__()`` returns an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will be invoked like\n   ``__init__(self[, ...])``, where *self* is the new instance and the\n   remaining arguments are the same as were passed to ``__new__()``.\n\n   If ``__new__()`` does not return an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will not be invoked.\n\n   ``__new__()`` is intended mainly to allow subclasses of immutable\n   types (like int, str, or tuple) to customize instance creation.  It\n   is also commonly overridden in custom metaclasses in order to\n   customize class creation.\n\nobject.__init__(self[, ...])\n\n   Called when the instance is created.  The arguments are those\n   passed to the class constructor expression.  If a base class has an\n   ``__init__()`` method, the derived class\'s ``__init__()`` method,\n   if any, must explicitly call it to ensure proper initialization of\n   the base class part of the instance; for example:\n   ``BaseClass.__init__(self, [args...])``.  As a special constraint\n   on constructors, no value may be returned; doing so will cause a\n   ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n   Called when the instance is about to be destroyed.  This is also\n   called a destructor.  If a base class has a ``__del__()`` method,\n   the derived class\'s ``__del__()`` method, if any, must explicitly\n   call it to ensure proper deletion of the base class part of the\n   instance.  Note that it is possible (though not recommended!) for\n   the ``__del__()`` method to postpone destruction of the instance by\n   creating a new reference to it.  It may then be called at a later\n   time when this new reference is deleted.  It is not guaranteed that\n   ``__del__()`` methods are called for objects that still exist when\n   the interpreter exits.\n\n   Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n     decrements the reference count for ``x`` by one, and the latter\n     is only called when ``x``\'s reference count reaches zero.  Some\n     common situations that may prevent the reference count of an\n     object from going to zero include: circular references between\n     objects (e.g., a doubly-linked list or a tree data structure with\n     parent and child pointers); a reference to the object on the\n     stack frame of a function that caught an exception (the traceback\n     stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n     a reference to the object on the stack frame that raised an\n     unhandled exception in interactive mode (the traceback stored in\n     ``sys.last_traceback`` keeps the stack frame alive).  The first\n     situation can only be remedied by explicitly breaking the cycles;\n     the latter two situations can be resolved by storing ``None`` in\n     ``sys.last_traceback``. Circular references which are garbage are\n     detected when the option cycle detector is enabled (it\'s on by\n     default), but can only be cleaned up if there are no Python-\n     level ``__del__()`` methods involved. Refer to the documentation\n     for the ``gc`` module for more information about how\n     ``__del__()`` methods are handled by the cycle detector,\n     particularly the description of the ``garbage`` value.\n\n   Warning: Due to the precarious circumstances under which ``__del__()``\n     methods are invoked, exceptions that occur during their execution\n     are ignored, and a warning is printed to ``sys.stderr`` instead.\n     Also, when ``__del__()`` is invoked in response to a module being\n     deleted (e.g., when execution of the program is done), other\n     globals referenced by the ``__del__()`` method may already have\n     been deleted or in the process of being torn down (e.g. the\n     import machinery shutting down).  For this reason, ``__del__()``\n     methods should do the absolute minimum needed to maintain\n     external invariants.  Starting with version 1.5, Python\n     guarantees that globals whose name begins with a single\n     underscore are deleted from their module before other globals are\n     deleted; if no other references to such globals exist, this may\n     help in assuring that imported modules are still available at the\n     time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n   Called by the ``repr()`` built-in function to compute the\n   "official" string representation of an object.  If at all possible,\n   this should look like a valid Python expression that could be used\n   to recreate an object with the same value (given an appropriate\n   environment).  If this is not possible, a string of the form\n   ``<...some useful description...>`` should be returned. The return\n   value must be a string object. If a class defines ``__repr__()``\n   but not ``__str__()``, then ``__repr__()`` is also used when an\n   "informal" string representation of instances of that class is\n   required.\n\n   This is typically used for debugging, so it is important that the\n   representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n   Called by the ``str()`` built-in function and by the ``print()``\n   function to compute the "informal" string representation of an\n   object.  This differs from ``__repr__()`` in that it does not have\n   to be a valid Python expression: a more convenient or concise\n   representation may be used instead. The return value must be a\n   string object.\n\nobject.__bytes__(self)\n\n   Called by ``bytes()`` to compute a byte-string representation of an\n   object. This should return a ``bytes`` object.\n\nobject.__format__(self, format_spec)\n\n   Called by the ``format()`` built-in function (and by extension, the\n   ``format()`` method of class ``str``) to produce a "formatted"\n   string representation of an object. The ``format_spec`` argument is\n   a string that contains a description of the formatting options\n   desired. The interpretation of the ``format_spec`` argument is up\n   to the type implementing ``__format__()``, however most classes\n   will either delegate formatting to one of the built-in types, or\n   use a similar formatting option syntax.\n\n   See *Format Specification Mini-Language* for a description of the\n   standard formatting syntax.\n\n   The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n   These are the so-called "rich comparison" methods. The\n   correspondence between operator symbols and method names is as\n   follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n   ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n   ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n   ``x.__ge__(y)``.\n\n   A rich comparison method may return the singleton\n   ``NotImplemented`` if it does not implement the operation for a\n   given pair of arguments. By convention, ``False`` and ``True`` are\n   returned for a successful comparison. However, these methods can\n   return any value, so if the comparison operator is used in a\n   Boolean context (e.g., in the condition of an ``if`` statement),\n   Python will call ``bool()`` on the value to determine if the result\n   is true or false.\n\n   There are no implied relationships among the comparison operators.\n   The truth of ``x==y`` does not imply that ``x!=y`` is false.\n   Accordingly, when defining ``__eq__()``, one should also define\n   ``__ne__()`` so that the operators will behave as expected.  See\n   the paragraph on ``__hash__()`` for some important notes on\n   creating *hashable* objects which support custom comparison\n   operations and are usable as dictionary keys.\n\n   There are no swapped-argument versions of these methods (to be used\n   when the left argument does not support the operation but the right\n   argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n   other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n   reflection, and ``__eq__()`` and ``__ne__()`` are their own\n   reflection.\n\n   Arguments to rich comparison methods are never coerced.\n\n   To automatically generate ordering operations from a single root\n   operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n   Called by built-in function ``hash()`` and for operations on\n   members of hashed collections including ``set``, ``frozenset``, and\n   ``dict``.  ``__hash__()`` should return an integer.  The only\n   required property is that objects which compare equal have the same\n   hash value; it is advised to somehow mix together (e.g. using\n   exclusive or) the hash values for the components of the object that\n   also play a part in comparison of objects.\n\n   If a class does not define an ``__eq__()`` method it should not\n   define a ``__hash__()`` operation either; if it defines\n   ``__eq__()`` but not ``__hash__()``, its instances will not be\n   usable as items in hashable collections.  If a class defines\n   mutable objects and implements an ``__eq__()`` method, it should\n   not implement ``__hash__()``, since the implementation of hashable\n   collections requires that a key\'s hash value is immutable (if the\n   object\'s hash value changes, it will be in the wrong hash bucket).\n\n   User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n   by default; with them, all objects compare unequal (except with\n   themselves) and ``x.__hash__()`` returns an appropriate value such\n   that ``x == y`` implies both that ``x is y`` and ``hash(x) ==\n   hash(y)``.\n\n   Classes which inherit a ``__hash__()`` method from a parent class\n   but change the meaning of ``__eq__()`` such that the hash value\n   returned is no longer appropriate (e.g. by switching to a value-\n   based concept of equality instead of the default identity based\n   equality) can explicitly flag themselves as being unhashable by\n   setting ``__hash__ = None`` in the class definition. Doing so means\n   that not only will instances of the class raise an appropriate\n   ``TypeError`` when a program attempts to retrieve their hash value,\n   but they will also be correctly identified as unhashable when\n   checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n   which define their own ``__hash__()`` to explicitly raise\n   ``TypeError``).\n\n   If a class that overrides ``__eq__()`` needs to retain the\n   implementation of ``__hash__()`` from a parent class, the\n   interpreter must be told this explicitly by setting ``__hash__ =\n   <ParentClass>.__hash__``. Otherwise the inheritance of\n   ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n   explicitly set to ``None``.\n\n   Note: Note by default the ``__hash__()`` values of str, bytes and\n     datetime objects are "salted" with an unpredictable random value.\n     Although they remain constant within an individual Python\n     process, they are not predictable between repeated invocations of\n     Python.This is intended to provide protection against a denial-\n     of-service caused by carefully-chosen inputs that exploit the\n     worst case performance of a dict insertion, O(n^2) complexity.\n     See http://www.ocert.org/advisories/ocert-2011-003.html for\n     details.Changing hash values affects the order in which keys are\n     retrieved from a dict.  Note Python has never made guarantees\n     about this ordering (and it typically varies between 32-bit and\n     64-bit builds).See also ``PYTHONHASHSEED``.\n\n   Changed in version 3.3: Hash randomization is enabled by default.\n\nobject.__bool__(self)\n\n   Called to implement truth value testing and the built-in operation\n   ``bool()``; should return ``False`` or ``True``.  When this method\n   is not defined, ``__len__()`` is called, if it is defined, and the\n   object is considered true if its result is nonzero.  If a class\n   defines neither ``__len__()`` nor ``__bool__()``, all its instances\n   are considered true.\n',
+ 'customization': '\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n   Called to create a new instance of class *cls*.  ``__new__()`` is a\n   static method (special-cased so you need not declare it as such)\n   that takes the class of which an instance was requested as its\n   first argument.  The remaining arguments are those passed to the\n   object constructor expression (the call to the class).  The return\n   value of ``__new__()`` should be the new object instance (usually\n   an instance of *cls*).\n\n   Typical implementations create a new instance of the class by\n   invoking the superclass\'s ``__new__()`` method using\n   ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n   arguments and then modifying the newly-created instance as\n   necessary before returning it.\n\n   If ``__new__()`` returns an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will be invoked like\n   ``__init__(self[, ...])``, where *self* is the new instance and the\n   remaining arguments are the same as were passed to ``__new__()``.\n\n   If ``__new__()`` does not return an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will not be invoked.\n\n   ``__new__()`` is intended mainly to allow subclasses of immutable\n   types (like int, str, or tuple) to customize instance creation.  It\n   is also commonly overridden in custom metaclasses in order to\n   customize class creation.\n\nobject.__init__(self[, ...])\n\n   Called when the instance is created.  The arguments are those\n   passed to the class constructor expression.  If a base class has an\n   ``__init__()`` method, the derived class\'s ``__init__()`` method,\n   if any, must explicitly call it to ensure proper initialization of\n   the base class part of the instance; for example:\n   ``BaseClass.__init__(self, [args...])``.  As a special constraint\n   on constructors, no value may be returned; doing so will cause a\n   ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n   Called when the instance is about to be destroyed.  This is also\n   called a destructor.  If a base class has a ``__del__()`` method,\n   the derived class\'s ``__del__()`` method, if any, must explicitly\n   call it to ensure proper deletion of the base class part of the\n   instance.  Note that it is possible (though not recommended!) for\n   the ``__del__()`` method to postpone destruction of the instance by\n   creating a new reference to it.  It may then be called at a later\n   time when this new reference is deleted.  It is not guaranteed that\n   ``__del__()`` methods are called for objects that still exist when\n   the interpreter exits.\n\n   Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n     decrements the reference count for ``x`` by one, and the latter\n     is only called when ``x``\'s reference count reaches zero.  Some\n     common situations that may prevent the reference count of an\n     object from going to zero include: circular references between\n     objects (e.g., a doubly-linked list or a tree data structure with\n     parent and child pointers); a reference to the object on the\n     stack frame of a function that caught an exception (the traceback\n     stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n     a reference to the object on the stack frame that raised an\n     unhandled exception in interactive mode (the traceback stored in\n     ``sys.last_traceback`` keeps the stack frame alive).  The first\n     situation can only be remedied by explicitly breaking the cycles;\n     the latter two situations can be resolved by storing ``None`` in\n     ``sys.last_traceback``. Circular references which are garbage are\n     detected when the option cycle detector is enabled (it\'s on by\n     default), but can only be cleaned up if there are no Python-\n     level ``__del__()`` methods involved. Refer to the documentation\n     for the ``gc`` module for more information about how\n     ``__del__()`` methods are handled by the cycle detector,\n     particularly the description of the ``garbage`` value.\n\n   Warning: Due to the precarious circumstances under which ``__del__()``\n     methods are invoked, exceptions that occur during their execution\n     are ignored, and a warning is printed to ``sys.stderr`` instead.\n     Also, when ``__del__()`` is invoked in response to a module being\n     deleted (e.g., when execution of the program is done), other\n     globals referenced by the ``__del__()`` method may already have\n     been deleted or in the process of being torn down (e.g. the\n     import machinery shutting down).  For this reason, ``__del__()``\n     methods should do the absolute minimum needed to maintain\n     external invariants.  Starting with version 1.5, Python\n     guarantees that globals whose name begins with a single\n     underscore are deleted from their module before other globals are\n     deleted; if no other references to such globals exist, this may\n     help in assuring that imported modules are still available at the\n     time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n   Called by the ``repr()`` built-in function to compute the\n   "official" string representation of an object.  If at all possible,\n   this should look like a valid Python expression that could be used\n   to recreate an object with the same value (given an appropriate\n   environment).  If this is not possible, a string of the form\n   ``<...some useful description...>`` should be returned. The return\n   value must be a string object. If a class defines ``__repr__()``\n   but not ``__str__()``, then ``__repr__()`` is also used when an\n   "informal" string representation of instances of that class is\n   required.\n\n   This is typically used for debugging, so it is important that the\n   representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n   Called by the ``str()`` built-in function and by the ``print()``\n   function to compute the "informal" string representation of an\n   object.  This differs from ``__repr__()`` in that it does not have\n   to be a valid Python expression: a more convenient or concise\n   representation may be used instead. The return value must be a\n   string object.\n\nobject.__bytes__(self)\n\n   Called by ``bytes()`` to compute a byte-string representation of an\n   object. This should return a ``bytes`` object.\n\nobject.__format__(self, format_spec)\n\n   Called by the ``format()`` built-in function (and by extension, the\n   ``format()`` method of class ``str``) to produce a "formatted"\n   string representation of an object. The ``format_spec`` argument is\n   a string that contains a description of the formatting options\n   desired. The interpretation of the ``format_spec`` argument is up\n   to the type implementing ``__format__()``, however most classes\n   will either delegate formatting to one of the built-in types, or\n   use a similar formatting option syntax.\n\n   See *Format Specification Mini-Language* for a description of the\n   standard formatting syntax.\n\n   The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n   These are the so-called "rich comparison" methods. The\n   correspondence between operator symbols and method names is as\n   follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n   ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n   ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n   ``x.__ge__(y)``.\n\n   A rich comparison method may return the singleton\n   ``NotImplemented`` if it does not implement the operation for a\n   given pair of arguments. By convention, ``False`` and ``True`` are\n   returned for a successful comparison. However, these methods can\n   return any value, so if the comparison operator is used in a\n   Boolean context (e.g., in the condition of an ``if`` statement),\n   Python will call ``bool()`` on the value to determine if the result\n   is true or false.\n\n   There are no implied relationships among the comparison operators.\n   The truth of ``x==y`` does not imply that ``x!=y`` is false.\n   Accordingly, when defining ``__eq__()``, one should also define\n   ``__ne__()`` so that the operators will behave as expected.  See\n   the paragraph on ``__hash__()`` for some important notes on\n   creating *hashable* objects which support custom comparison\n   operations and are usable as dictionary keys.\n\n   There are no swapped-argument versions of these methods (to be used\n   when the left argument does not support the operation but the right\n   argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n   other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n   reflection, and ``__eq__()`` and ``__ne__()`` are their own\n   reflection.\n\n   Arguments to rich comparison methods are never coerced.\n\n   To automatically generate ordering operations from a single root\n   operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n   Called by built-in function ``hash()`` and for operations on\n   members of hashed collections including ``set``, ``frozenset``, and\n   ``dict``.  ``__hash__()`` should return an integer.  The only\n   required property is that objects which compare equal have the same\n   hash value; it is advised to somehow mix together (e.g. using\n   exclusive or) the hash values for the components of the object that\n   also play a part in comparison of objects.\n\n   If a class does not define an ``__eq__()`` method it should not\n   define a ``__hash__()`` operation either; if it defines\n   ``__eq__()`` but not ``__hash__()``, its instances will not be\n   usable as items in hashable collections.  If a class defines\n   mutable objects and implements an ``__eq__()`` method, it should\n   not implement ``__hash__()``, since the implementation of hashable\n   collections requires that a key\'s hash value is immutable (if the\n   object\'s hash value changes, it will be in the wrong hash bucket).\n\n   User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n   by default; with them, all objects compare unequal (except with\n   themselves) and ``x.__hash__()`` returns an appropriate value such\n   that ``x == y`` implies both that ``x is y`` and ``hash(x) ==\n   hash(y)``.\n\n   Classes which inherit a ``__hash__()`` method from a parent class\n   but change the meaning of ``__eq__()`` such that the hash value\n   returned is no longer appropriate (e.g. by switching to a value-\n   based concept of equality instead of the default identity based\n   equality) can explicitly flag themselves as being unhashable by\n   setting ``__hash__ = None`` in the class definition. Doing so means\n   that not only will instances of the class raise an appropriate\n   ``TypeError`` when a program attempts to retrieve their hash value,\n   but they will also be correctly identified as unhashable when\n   checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n   which define their own ``__hash__()`` to explicitly raise\n   ``TypeError``).\n\n   If a class that overrides ``__eq__()`` needs to retain the\n   implementation of ``__hash__()`` from a parent class, the\n   interpreter must be told this explicitly by setting ``__hash__ =\n   <ParentClass>.__hash__``. Otherwise the inheritance of\n   ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n   explicitly set to ``None``.\n\n   Note: By default, the ``__hash__()`` values of str, bytes and datetime\n     objects are "salted" with an unpredictable random value.\n     Although they remain constant within an individual Python\n     process, they are not predictable between repeated invocations of\n     Python.This is intended to provide protection against a denial-\n     of-service caused by carefully-chosen inputs that exploit the\n     worst case performance of a dict insertion, O(n^2) complexity.\n     See http://www.ocert.org/advisories/ocert-2011-003.html for\n     details.Changing hash values affects the iteration order of\n     dicts, sets and other mappings.  Python has never made guarantees\n     about this ordering (and it typically varies between 32-bit and\n     64-bit builds).See also ``PYTHONHASHSEED``.\n\n   Changed in version 3.3: Hash randomization is enabled by default.\n\nobject.__bool__(self)\n\n   Called to implement truth value testing and the built-in operation\n   ``bool()``; should return ``False`` or ``True``.  When this method\n   is not defined, ``__len__()`` is called, if it is defined, and the\n   object is considered true if its result is nonzero.  If a class\n   defines neither ``__len__()`` nor ``__bool__()``, all its instances\n   are considered true.\n',
  'debugger': '\n``pdb`` --- The Python Debugger\n*******************************\n\nThe module ``pdb`` defines an interactive source code debugger for\nPython programs.  It supports setting (conditional) breakpoints and\nsingle stepping at the source line level, inspection of stack frames,\nsource code listing, and evaluation of arbitrary Python code in the\ncontext of any stack frame.  It also supports post-mortem debugging\nand can be called under program control.\n\nThe debugger is extensible -- it is actually defined as the class\n``Pdb``. This is currently undocumented but easily understood by\nreading the source.  The extension interface uses the modules ``bdb``\nand ``cmd``.\n\nThe debugger\'s prompt is ``(Pdb)``. Typical usage to run a program\nunder control of the debugger is:\n\n   >>> import pdb\n   >>> import mymodule\n   >>> pdb.run(\'mymodule.test()\')\n   > <string>(0)?()\n   (Pdb) continue\n   > <string>(1)?()\n   (Pdb) continue\n   NameError: \'spam\'\n   > <string>(1)?()\n   (Pdb)\n\nChanged in version 3.3: Tab-completion via the ``readline`` module is\navailable for commands and command arguments, e.g. the current global\nand local names are offered as arguments of the ``print`` command.\n\n``pdb.py`` can also be invoked as a script to debug other scripts.\nFor example:\n\n   python3 -m pdb myscript.py\n\nWhen invoked as a script, pdb will automatically enter post-mortem\ndebugging if the program being debugged exits abnormally.  After post-\nmortem debugging (or after normal exit of the program), pdb will\nrestart the program.  Automatic restarting preserves pdb\'s state (such\nas breakpoints) and in most cases is more useful than quitting the\ndebugger upon program\'s exit.\n\nNew in version 3.2: ``pdb.py`` now accepts a ``-c`` option that\nexecutes commands as if given in a ``.pdbrc`` file, see *Debugger\nCommands*.\n\nThe typical usage to break into the debugger from a running program is\nto insert\n\n   import pdb; pdb.set_trace()\n\nat the location you want to break into the debugger.  You can then\nstep through the code following this statement, and continue running\nwithout the debugger using the ``continue`` command.\n\nThe typical usage to inspect a crashed program is:\n\n   >>> import pdb\n   >>> import mymodule\n   >>> mymodule.test()\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in ?\n     File "./mymodule.py", line 4, in test\n       test2()\n     File "./mymodule.py", line 3, in test2\n       print(spam)\n   NameError: spam\n   >>> pdb.pm()\n   > ./mymodule.py(3)test2()\n   -> print(spam)\n   (Pdb)\n\nThe module defines the following functions; each enters the debugger\nin a slightly different way:\n\npdb.run(statement, globals=None, locals=None)\n\n   Execute the *statement* (given as a string or a code object) under\n   debugger control.  The debugger prompt appears before any code is\n   executed; you can set breakpoints and type ``continue``, or you can\n   step through the statement using ``step`` or ``next`` (all these\n   commands are explained below).  The optional *globals* and *locals*\n   arguments specify the environment in which the code is executed; by\n   default the dictionary of the module ``__main__`` is used.  (See\n   the explanation of the built-in ``exec()`` or ``eval()``\n   functions.)\n\npdb.runeval(expression, globals=None, locals=None)\n\n   Evaluate the *expression* (given as a string or a code object)\n   under debugger control.  When ``runeval()`` returns, it returns the\n   value of the expression.  Otherwise this function is similar to\n   ``run()``.\n\npdb.runcall(function, *args, **kwds)\n\n   Call the *function* (a function or method object, not a string)\n   with the given arguments.  When ``runcall()`` returns, it returns\n   whatever the function call returned.  The debugger prompt appears\n   as soon as the function is entered.\n\npdb.set_trace()\n\n   Enter the debugger at the calling stack frame.  This is useful to\n   hard-code a breakpoint at a given point in a program, even if the\n   code is not otherwise being debugged (e.g. when an assertion\n   fails).\n\npdb.post_mortem(traceback=None)\n\n   Enter post-mortem debugging of the given *traceback* object.  If no\n   *traceback* is given, it uses the one of the exception that is\n   currently being handled (an exception must be being handled if the\n   default is to be used).\n\npdb.pm()\n\n   Enter post-mortem debugging of the traceback found in\n   ``sys.last_traceback``.\n\nThe ``run*`` functions and ``set_trace()`` are aliases for\ninstantiating the ``Pdb`` class and calling the method of the same\nname.  If you want to access further features, you have to do this\nyourself:\n\nclass class pdb.Pdb(completekey=\'tab\', stdin=None, stdout=None, skip=None, nosigint=False)\n\n   ``Pdb`` is the debugger class.\n\n   The *completekey*, *stdin* and *stdout* arguments are passed to the\n   underlying ``cmd.Cmd`` class; see the description there.\n\n   The *skip* argument, if given, must be an iterable of glob-style\n   module name patterns.  The debugger will not step into frames that\n   originate in a module that matches one of these patterns. [1]\n\n   By default, Pdb sets a handler for the SIGINT signal (which is sent\n   when the user presses Ctrl-C on the console) when you give a\n   ``continue`` command. This allows you to break into the debugger\n   again by pressing Ctrl-C.  If you want Pdb not to touch the SIGINT\n   handler, set *nosigint* tot true.\n\n   Example call to enable tracing with *skip*:\n\n      import pdb; pdb.Pdb(skip=[\'django.*\']).set_trace()\n\n   New in version 3.1: The *skip* argument.\n\n   New in version 3.2: The *nosigint* argument.  Previously, a SIGINT\n   handler was never set by Pdb.\n\n   run(statement, globals=None, locals=None)\n   runeval(expression, globals=None, locals=None)\n   runcall(function, *args, **kwds)\n   set_trace()\n\n      See the documentation for the functions explained above.\n\n\nDebugger Commands\n=================\n\nThe commands recognized by the debugger are listed below.  Most\ncommands can be abbreviated to one or two letters as indicated; e.g.\n``h(elp)`` means that either ``h`` or ``help`` can be used to enter\nthe help command (but not ``he`` or ``hel``, nor ``H`` or ``Help`` or\n``HELP``).  Arguments to commands must be separated by whitespace\n(spaces or tabs).  Optional arguments are enclosed in square brackets\n(``[]``) in the command syntax; the square brackets must not be typed.\nAlternatives in the command syntax are separated by a vertical bar\n(``|``).\n\nEntering a blank line repeats the last command entered.  Exception: if\nthe last command was a ``list`` command, the next 11 lines are listed.\n\nCommands that the debugger doesn\'t recognize are assumed to be Python\nstatements and are executed in the context of the program being\ndebugged.  Python statements can also be prefixed with an exclamation\npoint (``!``).  This is a powerful way to inspect the program being\ndebugged; it is even possible to change a variable or call a function.\nWhen an exception occurs in such a statement, the exception name is\nprinted but the debugger\'s state is not changed.\n\nThe debugger supports *aliases*.  Aliases can have parameters which\nallows one a certain level of adaptability to the context under\nexamination.\n\nMultiple commands may be entered on a single line, separated by\n``;;``.  (A single ``;`` is not used as it is the separator for\nmultiple commands in a line that is passed to the Python parser.)  No\nintelligence is applied to separating the commands; the input is split\nat the first ``;;`` pair, even if it is in the middle of a quoted\nstring.\n\nIf a file ``.pdbrc`` exists in the user\'s home directory or in the\ncurrent directory, it is read in and executed as if it had been typed\nat the debugger prompt.  This is particularly useful for aliases.  If\nboth files exist, the one in the home directory is read first and\naliases defined there can be overridden by the local file.\n\nChanged in version 3.2: ``.pdbrc`` can now contain commands that\ncontinue debugging, such as ``continue`` or ``next``.  Previously,\nthese commands had no effect.\n\nh(elp) [command]\n\n   Without argument, print the list of available commands.  With a\n   *command* as argument, print help about that command.  ``help pdb``\n   displays the full documentation (the docstring of the ``pdb``\n   module).  Since the *command* argument must be an identifier,\n   ``help exec`` must be entered to get help on the ``!`` command.\n\nw(here)\n\n   Print a stack trace, with the most recent frame at the bottom.  An\n   arrow indicates the current frame, which determines the context of\n   most commands.\n\nd(own) [count]\n\n   Move the current frame *count* (default one) levels down in the\n   stack trace (to a newer frame).\n\nu(p) [count]\n\n   Move the current frame *count* (default one) levels up in the stack\n   trace (to an older frame).\n\nb(reak) [([filename:]lineno | function) [, condition]]\n\n   With a *lineno* argument, set a break there in the current file.\n   With a *function* argument, set a break at the first executable\n   statement within that function.  The line number may be prefixed\n   with a filename and a colon, to specify a breakpoint in another\n   file (probably one that hasn\'t been loaded yet).  The file is\n   searched on ``sys.path``.  Note that each breakpoint is assigned a\n   number to which all the other breakpoint commands refer.\n\n   If a second argument is present, it is an expression which must\n   evaluate to true before the breakpoint is honored.\n\n   Without argument, list all breaks, including for each breakpoint,\n   the number of times that breakpoint has been hit, the current\n   ignore count, and the associated condition if any.\n\ntbreak [([filename:]lineno | function) [, condition]]\n\n   Temporary breakpoint, which is removed automatically when it is\n   first hit. The arguments are the same as for ``break``.\n\ncl(ear) [filename:lineno | bpnumber [bpnumber ...]]\n\n   With a *filename:lineno* argument, clear all the breakpoints at\n   this line. With a space separated list of breakpoint numbers, clear\n   those breakpoints. Without argument, clear all breaks (but first\n   ask confirmation).\n\ndisable [bpnumber [bpnumber ...]]\n\n   Disable the breakpoints given as a space separated list of\n   breakpoint numbers.  Disabling a breakpoint means it cannot cause\n   the program to stop execution, but unlike clearing a breakpoint, it\n   remains in the list of breakpoints and can be (re-)enabled.\n\nenable [bpnumber [bpnumber ...]]\n\n   Enable the breakpoints specified.\n\nignore bpnumber [count]\n\n   Set the ignore count for the given breakpoint number.  If count is\n   omitted, the ignore count is set to 0.  A breakpoint becomes active\n   when the ignore count is zero.  When non-zero, the count is\n   decremented each time the breakpoint is reached and the breakpoint\n   is not disabled and any associated condition evaluates to true.\n\ncondition bpnumber [condition]\n\n   Set a new *condition* for the breakpoint, an expression which must\n   evaluate to true before the breakpoint is honored.  If *condition*\n   is absent, any existing condition is removed; i.e., the breakpoint\n   is made unconditional.\n\ncommands [bpnumber]\n\n   Specify a list of commands for breakpoint number *bpnumber*.  The\n   commands themselves appear on the following lines.  Type a line\n   containing just ``end`` to terminate the commands. An example:\n\n      (Pdb) commands 1\n      (com) print some_variable\n      (com) end\n      (Pdb)\n\n   To remove all commands from a breakpoint, type commands and follow\n   it immediately with ``end``; that is, give no commands.\n\n   With no *bpnumber* argument, commands refers to the last breakpoint\n   set.\n\n   You can use breakpoint commands to start your program up again.\n   Simply use the continue command, or step, or any other command that\n   resumes execution.\n\n   Specifying any command resuming execution (currently continue,\n   step, next, return, jump, quit and their abbreviations) terminates\n   the command list (as if that command was immediately followed by\n   end). This is because any time you resume execution (even with a\n   simple next or step), you may encounter another breakpoint--which\n   could have its own command list, leading to ambiguities about which\n   list to execute.\n\n   If you use the \'silent\' command in the command list, the usual\n   message about stopping at a breakpoint is not printed.  This may be\n   desirable for breakpoints that are to print a specific message and\n   then continue.  If none of the other commands print anything, you\n   see no sign that the breakpoint was reached.\n\ns(tep)\n\n   Execute the current line, stop at the first possible occasion\n   (either in a function that is called or on the next line in the\n   current function).\n\nn(ext)\n\n   Continue execution until the next line in the current function is\n   reached or it returns.  (The difference between ``next`` and\n   ``step`` is that ``step`` stops inside a called function, while\n   ``next`` executes called functions at (nearly) full speed, only\n   stopping at the next line in the current function.)\n\nunt(il) [lineno]\n\n   Without argument, continue execution until the line with a number\n   greater than the current one is reached.\n\n   With a line number, continue execution until a line with a number\n   greater or equal to that is reached.  In both cases, also stop when\n   the current frame returns.\n\n   Changed in version 3.2: Allow giving an explicit line number.\n\nr(eturn)\n\n   Continue execution until the current function returns.\n\nc(ont(inue))\n\n   Continue execution, only stop when a breakpoint is encountered.\n\nj(ump) lineno\n\n   Set the next line that will be executed.  Only available in the\n   bottom-most frame.  This lets you jump back and execute code again,\n   or jump forward to skip code that you don\'t want to run.\n\n   It should be noted that not all jumps are allowed -- for instance\n   it is not possible to jump into the middle of a ``for`` loop or out\n   of a ``finally`` clause.\n\nl(ist) [first[, last]]\n\n   List source code for the current file.  Without arguments, list 11\n   lines around the current line or continue the previous listing.\n   With ``.`` as argument, list 11 lines around the current line.\n   With one argument, list 11 lines around at that line.  With two\n   arguments, list the given range; if the second argument is less\n   than the first, it is interpreted as a count.\n\n   The current line in the current frame is indicated by ``->``.  If\n   an exception is being debugged, the line where the exception was\n   originally raised or propagated is indicated by ``>>``, if it\n   differs from the current line.\n\n   New in version 3.2: The ``>>`` marker.\n\nll | longlist\n\n   List all source code for the current function or frame.\n   Interesting lines are marked as for ``list``.\n\n   New in version 3.2.\n\na(rgs)\n\n   Print the argument list of the current function.\n\np(rint) expression\n\n   Evaluate the *expression* in the current context and print its\n   value.\n\npp expression\n\n   Like the ``print`` command, except the value of the expression is\n   pretty-printed using the ``pprint`` module.\n\nwhatis expression\n\n   Print the type of the *expression*.\n\nsource expression\n\n   Try to get source code for the given object and display it.\n\n   New in version 3.2.\n\ndisplay [expression]\n\n   Display the value of the expression if it changed, each time\n   execution stops in the current frame.\n\n   Without expression, list all display expressions for the current\n   frame.\n\n   New in version 3.2.\n\nundisplay [expression]\n\n   Do not display the expression any more in the current frame.\n   Without expression, clear all display expressions for the current\n   frame.\n\n   New in version 3.2.\n\ninteract\n\n   Start an interative interpreter (using the ``code`` module) whose\n   global namespace contains all the (global and local) names found in\n   the current scope.\n\n   New in version 3.2.\n\nalias [name [command]]\n\n   Create an alias called *name* that executes *command*.  The command\n   must *not* be enclosed in quotes.  Replaceable parameters can be\n   indicated by ``%1``, ``%2``, and so on, while ``%*`` is replaced by\n   all the parameters. If no command is given, the current alias for\n   *name* is shown. If no arguments are given, all aliases are listed.\n\n   Aliases may be nested and can contain anything that can be legally\n   typed at the pdb prompt.  Note that internal pdb commands *can* be\n   overridden by aliases.  Such a command is then hidden until the\n   alias is removed.  Aliasing is recursively applied to the first\n   word of the command line; all other words in the line are left\n   alone.\n\n   As an example, here are two useful aliases (especially when placed\n   in the ``.pdbrc`` file):\n\n      # Print instance variables (usage "pi classInst")\n      alias pi for k in %1.__dict__.keys(): print("%1.",k,"=",%1.__dict__[k])\n      # Print instance variables in self\n      alias ps pi self\n\nunalias name\n\n   Delete the specified alias.\n\n! statement\n\n   Execute the (one-line) *statement* in the context of the current\n   stack frame. The exclamation point can be omitted unless the first\n   word of the statement resembles a debugger command.  To set a\n   global variable, you can prefix the assignment command with a\n   ``global`` statement on the same line, e.g.:\n\n      (Pdb) global list_options; list_options = [\'-l\']\n      (Pdb)\n\nrun [args ...]\nrestart [args ...]\n\n   Restart the debugged Python program.  If an argument is supplied,\n   it is split with ``shlex`` and the result is used as the new\n   ``sys.argv``. History, breakpoints, actions and debugger options\n   are preserved. ``restart`` is an alias for ``run``.\n\nq(uit)\n\n   Quit from the debugger.  The program being executed is aborted.\n\n-[ Footnotes ]-\n\n[1] Whether a frame is considered to originate in a certain module is\n    determined by the ``__name__`` in the frame globals.\n',
  'del': '\nThe ``del`` statement\n*********************\n\n   del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather than spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block.  If the name is unbound, a\n``NameError`` exception will be raised.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n\nChanged in version 3.2: Previously it was illegal to delete a name\nfrom the local namespace if it occurs as a free variable in a nested\nblock.\n',
  'dict': '\nDictionary displays\n*******************\n\nA dictionary display is a possibly empty series of key/datum pairs\nenclosed in curly braces:\n\n   dict_display       ::= "{" [key_datum_list | dict_comprehension] "}"\n   key_datum_list     ::= key_datum ("," key_datum)* [","]\n   key_datum          ::= expression ":" expression\n   dict_comprehension ::= expression ":" expression comp_for\n\nA dictionary display yields a new dictionary object.\n\nIf a comma-separated sequence of key/datum pairs is given, they are\nevaluated from left to right to define the entries of the dictionary:\neach key object is used as a key into the dictionary to store the\ncorresponding datum.  This means that you can specify the same key\nmultiple times in the key/datum list, and the final dictionary\'s value\nfor that key will be the last one given.\n\nA dict comprehension, in contrast to list and set comprehensions,\nneeds two expressions separated with a colon followed by the usual\n"for" and "if" clauses. When the comprehension is run, the resulting\nkey and value elements are inserted in the new dictionary in the order\nthey are produced.\n\nRestrictions on the types of the key values are listed earlier in\nsection *The standard type hierarchy*.  (To summarize, the key type\nshould be *hashable*, which excludes all mutable objects.)  Clashes\nbetween duplicate keys are not detected; the last datum (textually\nrightmost in the display) stored for a given key value prevails.\n',
@@ -41,7 +41,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss
  'identifiers': '\nIdentifiers and keywords\n************************\n\nIdentifiers (also referred to as *names*) are described by the\nfollowing lexical definitions.\n\nThe syntax of identifiers in Python is based on the Unicode standard\nannex UAX-31, with elaboration and changes as defined below; see also\n**PEP 3131** for further details.\n\nWithin the ASCII range (U+0001..U+007F), the valid characters for\nidentifiers are the same as in Python 2.x: the uppercase and lowercase\nletters ``A`` through ``Z``, the underscore ``_`` and, except for the\nfirst character, the digits ``0`` through ``9``.\n\nPython 3.0 introduces additional characters from outside the ASCII\nrange (see **PEP 3131**).  For these characters, the classification\nuses the version of the Unicode Character Database as included in the\n``unicodedata`` module.\n\nIdentifiers are unlimited in length.  Case is significant.\n\n   identifier   ::= xid_start xid_continue*\n   id_start     ::= <all characters in general categories Lu, Ll, Lt, Lm, Lo, Nl, the underscore, and characters with the Other_ID_Start property>\n   id_continue  ::= <all characters in id_start, plus characters in the categories Mn, Mc, Nd, Pc and others with the Other_ID_Continue property>\n   xid_start    ::= <all characters in id_start whose NFKC normalization is in "id_start xid_continue*">\n   xid_continue ::= <all characters in id_continue whose NFKC normalization is in "id_continue*">\n\nThe Unicode category codes mentioned above stand for:\n\n* *Lu* - uppercase letters\n\n* *Ll* - lowercase letters\n\n* *Lt* - titlecase letters\n\n* *Lm* - modifier letters\n\n* *Lo* - other letters\n\n* *Nl* - letter numbers\n\n* *Mn* - nonspacing marks\n\n* *Mc* - spacing combining marks\n\n* *Nd* - decimal numbers\n\n* *Pc* - connector punctuations\n\n* *Other_ID_Start* - explicit list of characters in PropList.txt to\n  support backwards compatibility\n\n* *Other_ID_Continue* - likewise\n\nAll identifiers are converted into the normal form NFKC while parsing;\ncomparison of identifiers is based on NFKC.\n\nA non-normative HTML file listing all valid identifier characters for\nUnicode 4.1 can be found at http://www.dcl.hpi.uni-\npotsdam.de/home/loewis/table-3131.html.\n\n\nKeywords\n========\n\nThe following identifiers are used as reserved words, or *keywords* of\nthe language, and cannot be used as ordinary identifiers.  They must\nbe spelled exactly as written here:\n\n   False      class      finally    is         return\n   None       continue   for        lambda     try\n   True       def        from       nonlocal   while\n   and        del        global     not        with\n   as         elif       if         or         yield\n   assert     else       import     pass\n   break      except     in         raise\n\n\nReserved classes of identifiers\n===============================\n\nCertain classes of identifiers (besides keywords) have special\nmeanings.  These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n   Not imported by ``from module import *``.  The special identifier\n   ``_`` is used in the interactive interpreter to store the result of\n   the last evaluation; it is stored in the ``builtins`` module.  When\n   not in interactive mode, ``_`` has no special meaning and is not\n   defined. See section *The import statement*.\n\n   Note: The name ``_`` is often used in conjunction with\n     internationalization; refer to the documentation for the\n     ``gettext`` module for more information on this convention.\n\n``__*__``\n   System-defined names. These names are defined by the interpreter\n   and its implementation (including the standard library).  Current\n   system names are discussed in the *Special method names* section\n   and elsewhere.  More will likely be defined in future versions of\n   Python.  *Any* use of ``__*__`` names, in any context, that does\n   not follow explicitly documented use, is subject to breakage\n   without warning.\n\n``__*``\n   Class-private names.  Names in this category, when used within the\n   context of a class definition, are re-written to use a mangled form\n   to help avoid name clashes between "private" attributes of base and\n   derived classes. See section *Identifiers (Names)*.\n',
  'if': '\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n   if_stmt ::= "if" expression ":" suite\n               ( "elif" expression ":" suite )*\n               ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n',
  'imaginary': '\nImaginary literals\n******************\n\nImaginary literals are described by the following lexical definitions:\n\n   imagnumber ::= (floatnumber | intpart) ("j" | "J")\n\nAn imaginary literal yields a complex number with a real part of 0.0.\nComplex numbers are represented as a pair of floating point numbers\nand have the same restrictions on their range.  To create a complex\nnumber with a nonzero real part, add a floating point number to it,\ne.g., ``(3+4j)``.  Some examples of imaginary literals:\n\n   3.14j   10.j    10j     .001j   1e100j  3.14e-10j\n',
- 'import': '\nThe ``import`` statement\n************************\n\n   import_stmt     ::= "import" module ["as" name] ( "," module ["as" name] )*\n                   | "from" relative_module "import" identifier ["as" name]\n                   ( "," identifier ["as" name] )*\n                   | "from" relative_module "import" "(" identifier ["as" name]\n                   ( "," identifier ["as" name] )* [","] ")"\n                   | "from" module "import" "*"\n   module          ::= (identifier ".")* identifier\n   relative_module ::= "."* module | "."+\n   name            ::= identifier\n\nImport statements are executed in two steps: (1) find a module, and\ninitialize it if necessary; (2) define a name or names in the local\nnamespace (of the scope where the ``import`` statement occurs). The\nstatement comes in two forms differing on whether it uses the ``from``\nkeyword. The first form (without ``from``) repeats these steps for\neach identifier in the list. The form with ``from`` performs step (1)\nonce, and then performs step (2) repeatedly. For a reference\nimplementation of step (1), see the ``importlib`` module.\n\nTo understand how step (1) occurs, one must first understand how\nPython handles hierarchical naming of modules. To help organize\nmodules and provide a hierarchy in naming, Python has a concept of\npackages. A package can contain other packages and modules while\nmodules cannot contain other modules or packages. From a file system\nperspective, packages are directories and modules are files. The\noriginal specification for packages is still available to read,\nalthough minor details have changed since the writing of that\ndocument.\n\nOnce the name of the module is known (unless otherwise specified, the\nterm "module" will refer to both packages and modules), searching for\nthe module or package can begin. The first place checked is\n``sys.modules``, the cache of all modules that have been imported\npreviously. If the module is found there then it is used in step (2)\nof import unless ``None`` is found in ``sys.modules``, in which case\n``ImportError`` is raised.\n\nIf the module is not found in the cache, then ``sys.meta_path`` is\nsearched (the specification for ``sys.meta_path`` can be found in\n**PEP 302**). The object is a list of *finder* objects which are\nqueried in order as to whether they know how to load the module by\ncalling their ``find_module()`` method with the name of the module. If\nthe module happens to be contained within a package (as denoted by the\nexistence of a dot in the name), then a second argument to\n``find_module()`` is given as the value of the ``__path__`` attribute\nfrom the parent package (everything up to the last dot in the name of\nthe module being imported). If a finder can find the module it returns\na *loader* (discussed later) or returns ``None``.\n\nIf none of the finders on ``sys.meta_path`` are able to find the\nmodule then some implicitly defined finders are queried.\nImplementations of Python vary in what implicit meta path finders are\ndefined. The one they all do define, though, is one that handles\n``sys.path_hooks``, ``sys.path_importer_cache``, and ``sys.path``.\n\nThe implicit finder searches for the requested module in the "paths"\nspecified in one of two places ("paths" do not have to be file system\npaths). If the module being imported is supposed to be contained\nwithin a package then the second argument passed to ``find_module()``,\n``__path__`` on the parent package, is used as the source of paths. If\nthe module is not contained in a package then ``sys.path`` is used as\nthe source of paths.\n\nOnce the source of paths is chosen it is iterated over to find a\nfinder that can handle that path. The dict at\n``sys.path_importer_cache`` caches finders for paths and is checked\nfor a finder. If the path does not have a finder cached then\n``sys.path_hooks`` is searched by calling each object in the list with\na single argument of the path, returning a finder or raises\n``ImportError``. If a finder is returned then it is cached in\n``sys.path_importer_cache`` and then used for that path entry. If no\nfinder can be found but the path exists then a value of ``None`` is\nstored in ``sys.path_importer_cache`` to signify that an implicit,\nfile-based finder that handles modules stored as individual files\nshould be used for that path. If the path does not exist then a finder\nwhich always returns ``None`` is placed in the cache for the path.\n\nIf no finder can find the module then ``ImportError`` is raised.\nOtherwise some finder returned a loader whose ``load_module()`` method\nis called with the name of the module to load (see **PEP 302** for the\noriginal definition of loaders). A loader has several responsibilities\nto perform on a module it loads. First, if the module already exists\nin ``sys.modules`` (a possibility if the loader is called outside of\nthe import machinery) then it is to use that module for initialization\nand not a new module. But if the module does not exist in\n``sys.modules`` then it is to be added to that dict before\ninitialization begins. If an error occurs during loading of the module\nand it was added to ``sys.modules`` it is to be removed from the dict.\nIf an error occurs but the module was already in ``sys.modules`` it is\nleft in the dict.\n\nThe loader must set several attributes on the module. ``__name__`` is\nto be set to the name of the module. ``__file__`` is to be the "path"\nto the file unless the module is built-in (and thus listed in\n``sys.builtin_module_names``) in which case the attribute is not set.\nIf what is being imported is a package then ``__path__`` is to be set\nto a list of paths to be searched when looking for modules and\npackages contained within the package being imported. ``__package__``\nis optional but should be set to the name of package that contains the\nmodule or package (the empty string is used for module not contained\nin a package). ``__loader__`` is also optional but should be set to\nthe loader object that is loading the module. While loaders are\nrequired to return the module they loaded, import itself always\nretrieves any modules it returns from ``sys.modules``.\n\nIf an error occurs during loading then the loader raises\n``ImportError`` if some other exception is not already being\npropagated. Otherwise the loader returns the module that was loaded\nand initialized.\n\nWhen step (1) finishes without raising an exception, step (2) can\nbegin.\n\nThe first form of ``import`` statement binds the module name in the\nlocal namespace to the module object, and then goes on to import the\nnext identifier, if any.  If the module name is followed by ``as``,\nthe name following ``as`` is used as the local name for the module.\n\nThe ``from`` form does not bind the module name: it goes through the\nlist of identifiers, looks each one of them up in the module found in\nstep (1), and binds the name in the local namespace to the object thus\nfound.  As with the first form of ``import``, an alternate local name\ncan be supplied by specifying "``as`` localname".  If a name is not\nfound, ``ImportError`` is raised.  If the list of identifiers is\nreplaced by a star (``\'*\'``), all public names defined in the module\nare bound in the local namespace of the ``import`` statement.\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named ``__all__``; if defined, it\nmust be a sequence of strings which are names defined or imported by\nthat module.  The names given in ``__all__`` are all considered public\nand are required to exist.  If ``__all__`` is not defined, the set of\npublic names includes all names found in the module\'s namespace which\ndo not begin with an underscore character (``\'_\'``). ``__all__``\nshould contain the entire public API. It is intended to avoid\naccidentally exporting items that are not part of the API (such as\nlibrary modules which were imported and used within the module).\n\nThe ``from`` form with ``*`` may only occur in a module scope.  The\nwild card form of import --- ``import *`` --- is only allowed at the\nmodule level. Attempting to use it in class or function definitions\nwill raise a ``SyntaxError``.\n\nWhen specifying what module to import you do not have to specify the\nabsolute name of the module. When a module or package is contained\nwithin another package it is possible to make a relative import within\nthe same top package without having to mention the package name. By\nusing leading dots in the specified module or package after ``from``\nyou can specify how high to traverse up the current package hierarchy\nwithout specifying exact names. One leading dot means the current\npackage where the module making the import exists. Two dots means up\none package level. Three dots is up two levels, etc. So if you execute\n``from . import mod`` from a module in the ``pkg`` package then you\nwill end up importing ``pkg.mod``. If you execute ``from ..subpkg2\nimport mod`` from within ``pkg.subpkg1`` you will import\n``pkg.subpkg2.mod``. The specification for relative imports is\ncontained within **PEP 328**.\n\n``importlib.import_module()`` is provided to support applications that\ndetermine which modules need to be loaded dynamically.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python.  The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language.  It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n   future_statement ::= "from" "__future__" "import" feature ["as" name]\n                        ("," feature ["as" name])*\n                        | "from" "__future__" "import" "(" feature ["as" name]\n                        ("," feature ["as" name])* [","] ")"\n   feature          ::= identifier\n   name             ::= identifier\n\nA future statement must appear near the top of the module.  The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 3.0 are ``absolute_import``,\n``division``, ``generators``, ``unicode_literals``,\n``print_function``, ``nested_scopes`` and ``with_statement``.  They\nare all redundant because they are always enabled, and only kept for\nbackwards compatibility.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code.  It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently.  Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n   import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by calls to the built-in functions ``exec()`` and\n``compile()`` that occur in a module ``M`` containing a future\nstatement will, by default, use the new syntax or semantics associated\nwith the future statement.  This can be controlled by optional\narguments to ``compile()`` --- see the documentation of that function\nfor details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session.  If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\nSee also:\n\n   **PEP 236** - Back to the __future__\n      The original proposal for the __future__ mechanism.\n',
+ 'import': '\nThe ``import`` statement\n************************\n\n   import_stmt     ::= "import" module ["as" name] ( "," module ["as" name] )*\n                   | "from" relative_module "import" identifier ["as" name]\n                   ( "," identifier ["as" name] )*\n                   | "from" relative_module "import" "(" identifier ["as" name]\n                   ( "," identifier ["as" name] )* [","] ")"\n                   | "from" module "import" "*"\n   module          ::= (identifier ".")* identifier\n   relative_module ::= "."* module | "."+\n   name            ::= identifier\n\nThe basic import statement (no ``from`` clause) is executed in two\nsteps:\n\n1. find a module, loading and initializing it if necessary\n\n2. define a name or names in the local namespace for the scope where\n   the ``import`` statement occurs.\n\nWhen the statement contains multiple clauses (separated by commas) the\ntwo steps are carried out separately for each clause, just as though\nthe clauses had been separated out into individiual import statements.\n\nThe details of the first step, finding and loading modules is\ndescribed in greater detail in the section on the *import system*,\nwhich also describes the various types of packages and modules that\ncan be imported, as well as all the hooks that can be used to\ncustomize the import system. Note that failures in this step may\nindicate either that the module could not be located, *or* that an\nerror occurred while initializing the module, which includes execution\nof the module\'s code.\n\nIf the requested module is retrieved successfully, it will be made\navailable in the local namespace in one of three ways:\n\n* If the module name is followed by ``as``, then the name following\n  ``as`` is bound directly to the imported module.\n\n* If no other name is specified, and the module being imported is a\n  top level module, the module\'s name is bound in the local namespace\n  as a reference to the imported module\n\n* If the module being imported is *not* a top level module, then the\n  name of the top level package that contains the module is bound in\n  the local namespace as a reference to the top level package. The\n  imported module must be accessed using its full qualified name\n  rather than directly\n\nThe ``from`` form uses a slightly more complex process:\n\n1. find the module specified in the ``from`` clause loading and\n   initializing it if necessary;\n\n2. for each of the identifiers specified in the ``import`` clauses:\n\n   1. check if the imported module has an attribute by that name\n\n   2. if not, attempt to import a submodule with that name and then\n      check the imported module again for that attribute\n\n   3. if the attribute is not found, ``ImportError`` is raised.\n\n   4. otherwise, a reference to that value is bound in the local\n      namespace, using the name in the ``as`` clause if it is present,\n      otherwise using the attribute name\n\nExamples:\n\n   import foo                 # foo imported and bound locally\n   import foo.bar.baz         # foo.bar.baz imported, foo bound locally\n   import foo.bar.baz as fbb  # foo.bar.baz imported and bound as fbb\n   from foo.bar import baz    # foo.bar.baz imported and bound as baz\n   from foo import attr       # foo imported and foo.attr bound as attr\n\nIf the list of identifiers is replaced by a star (``\'*\'``), all public\nnames defined in the module are bound in the local namespace for the\nscope where the ``import`` statement occurs.\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named ``__all__``; if defined, it\nmust be a sequence of strings which are names defined or imported by\nthat module.  The names given in ``__all__`` are all considered public\nand are required to exist.  If ``__all__`` is not defined, the set of\npublic names includes all names found in the module\'s namespace which\ndo not begin with an underscore character (``\'_\'``).  ``__all__``\nshould contain the entire public API. It is intended to avoid\naccidentally exporting items that are not part of the API (such as\nlibrary modules which were imported and used within the module).\n\nThe ``from`` form with ``*`` may only occur in a module scope.\nAttempting to use it in class or function definitions will raise a\n``SyntaxError``.\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named ``__all__``; if defined, it\nmust be a sequence of strings which are names defined or imported by\nthat module.  The names given in ``__all__`` are all considered public\nand are required to exist.  If ``__all__`` is not defined, the set of\npublic names includes all names found in the module\'s namespace which\ndo not begin with an underscore character (``\'_\'``).  ``__all__``\nshould contain the entire public API. It is intended to avoid\naccidentally exporting items that are not part of the API (such as\nlibrary modules which were imported and used within the module).\n\nThe ``from`` form with ``*`` may only occur in a module scope.  The\nwild card form of import --- ``import *`` --- is only allowed at the\nmodule level. Attempting to use it in class or function definitions\nwill raise a ``SyntaxError``.\n\nWhen specifying what module to import you do not have to specify the\nabsolute name of the module. When a module or package is contained\nwithin another package it is possible to make a relative import within\nthe same top package without having to mention the package name. By\nusing leading dots in the specified module or package after ``from``\nyou can specify how high to traverse up the current package hierarchy\nwithout specifying exact names. One leading dot means the current\npackage where the module making the import exists. Two dots means up\none package level. Three dots is up two levels, etc. So if you execute\n``from . import mod`` from a module in the ``pkg`` package then you\nwill end up importing ``pkg.mod``. If you execute ``from ..subpkg2\nimport mod`` from within ``pkg.subpkg1`` you will import\n``pkg.subpkg2.mod``. The specification for relative imports is\ncontained within **PEP 328**.\n\n``importlib.import_module()`` is provided to support applications that\ndetermine which modules need to be loaded dynamically.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python.  The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language.  It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n   future_statement ::= "from" "__future__" "import" feature ["as" name]\n                        ("," feature ["as" name])*\n                        | "from" "__future__" "import" "(" feature ["as" name]\n                        ("," feature ["as" name])* [","] ")"\n   feature          ::= identifier\n   name             ::= identifier\n\nA future statement must appear near the top of the module.  The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 3.0 are ``absolute_import``,\n``division``, ``generators``, ``unicode_literals``,\n``print_function``, ``nested_scopes`` and ``with_statement``.  They\nare all redundant because they are always enabled, and only kept for\nbackwards compatibility.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code.  It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently.  Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n   import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by calls to the built-in functions ``exec()`` and\n``compile()`` that occur in a module ``M`` containing a future\nstatement will, by default, use the new syntax or semantics associated\nwith the future statement.  This can be controlled by optional\narguments to ``compile()`` --- see the documentation of that function\nfor details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session.  If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\nSee also:\n\n   **PEP 236** - Back to the __future__\n      The original proposal for the __future__ mechanism.\n',
  'in': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation.  Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n   comparison    ::= or_expr ( comp_operator or_expr )*\n   comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n                     | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects.  The objects need not have the same type.\nIf both are numbers, they are converted to a common type.  Otherwise,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes.  You can control comparison behavior of objects of non-built-in\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n  are identical to themselves, ``x is x`` but are not equal to\n  themselves, ``x != x``.  Additionally, comparing any value to a\n  not-a-number value will return ``False``.  For example, both ``3 <\n  float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n  values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n  (the result of the built-in function ``ord()``) of their characters.\n  [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison of\n  corresponding elements.  This means that to compare equal, each\n  element must compare equal and the two sequences must be of the same\n  type and have the same length.\n\n  If not equal, the sequences are ordered the same as their first\n  differing elements.  For example, ``[1,2,x] <= [1,2,y]`` has the\n  same value as ``x <= y``.  If the corresponding element does not\n  exist, the shorter sequence is ordered first (for example, ``[1,2] <\n  [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if they have the\n  same ``(key, value)`` pairs. Order comparisons ``(\'<\', \'<=\', \'>=\',\n  \'>\')`` raise ``TypeError``.\n\n* Sets and frozensets define comparison operators to mean subset and\n  superset tests.  Those relations do not define total orderings (the\n  two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n  another, nor supersets of one another).  Accordingly, sets are not\n  appropriate arguments for functions which depend on total ordering.\n  For example, ``min()``, ``max()``, and ``sorted()`` produce\n  undefined results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they are\n  the same object; the choice whether one object is considered smaller\n  or larger than another one is made arbitrarily but consistently\n  within one execution of a program.\n\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison.  Most\nnumeric types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is.  When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``.  This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons.  For example, ``Decimal(2) ==\n2`` and ``2 == float(2)`` but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership.  ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise.  ``x\nnot in s`` returns the negation of ``x in s``.  All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` is equivalent to ``any(x is e or x == e for e in\ny)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*.  An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` but do\ndefine ``__iter__()``, ``x in y`` is true if some value ``z`` with ``x\n== z`` is produced while iterating over ``y``.  If an exception is\nraised during the iteration, it is as if ``in`` raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n``__getitem__()``, ``x in y`` is true if and only if there is a non-\nnegative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception.  (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object.  ``x is\nnot y`` yields the inverse truth value. [4]\n',
  'integers': '\nInteger literals\n****************\n\nInteger literals are described by the following lexical definitions:\n\n   integer        ::= decimalinteger | octinteger | hexinteger | bininteger\n   decimalinteger ::= nonzerodigit digit* | "0"+\n   nonzerodigit   ::= "1"..."9"\n   digit          ::= "0"..."9"\n   octinteger     ::= "0" ("o" | "O") octdigit+\n   hexinteger     ::= "0" ("x" | "X") hexdigit+\n   bininteger     ::= "0" ("b" | "B") bindigit+\n   octdigit       ::= "0"..."7"\n   hexdigit       ::= digit | "a"..."f" | "A"..."F"\n   bindigit       ::= "0" | "1"\n\nThere is no limit for the length of integer literals apart from what\ncan be stored in available memory.\n\nNote that leading zeros in a non-zero decimal number are not allowed.\nThis is for disambiguation with C-style octal literals, which Python\nused before version 3.0.\n\nSome examples of integer literals:\n\n   7     2147483647                        0o177    0b100110111\n   3     79228162514264337593543950336     0o377    0x100000000\n         79228162514264337593543950336              0xdeadbeef\n',
  'lambda': '\nLambdas\n*******\n\n   lambda_form        ::= "lambda" [parameter_list]: expression\n   lambda_form_nocond ::= "lambda" [parameter_list]: expression_nocond\n\nLambda forms (lambda expressions) have the same syntactic position as\nexpressions.  They are a shorthand to create anonymous functions; the\nexpression ``lambda arguments: expression`` yields a function object.\nThe unnamed object behaves like a function object defined with\n\n   def <lambda>(arguments):\n       return expression\n\nSee section *Function definitions* for the syntax of parameter lists.\nNote that functions created with lambda forms cannot contain\nstatements or annotations.\n',
@@ -60,18 +60,18 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss
  'shifting': '\nShifting operations\n*******************\n\nThe shifting operations have lower priority than the arithmetic\noperations:\n\n   shift_expr ::= a_expr | shift_expr ( "<<" | ">>" ) a_expr\n\nThese operators accept integers as arguments.  They shift the first\nargument to the left or right by the number of bits given by the\nsecond argument.\n\nA right shift by *n* bits is defined as division by ``pow(2,n)``.  A\nleft shift by *n* bits is defined as multiplication with ``pow(2,n)``.\n\nNote: In the current implementation, the right-hand operand is required to\n  be at most ``sys.maxsize``.  If the right-hand operand is larger\n  than ``sys.maxsize`` an ``OverflowError`` exception is raised.\n',
  'slicings': '\nSlicings\n********\n\nA slicing selects a range of items in a sequence object (e.g., a\nstring, tuple or list).  Slicings may be used as expressions or as\ntargets in assignment or ``del`` statements.  The syntax for a\nslicing:\n\n   slicing      ::= primary "[" slice_list "]"\n   slice_list   ::= slice_item ("," slice_item)* [","]\n   slice_item   ::= expression | proper_slice\n   proper_slice ::= [lower_bound] ":" [upper_bound] [ ":" [stride] ]\n   lower_bound  ::= expression\n   upper_bound  ::= expression\n   stride       ::= expression\n\nThere is ambiguity in the formal syntax here: anything that looks like\nan expression list also looks like a slice list, so any subscription\ncan be interpreted as a slicing.  Rather than further complicating the\nsyntax, this is disambiguated by defining that in this case the\ninterpretation as a subscription takes priority over the\ninterpretation as a slicing (this is the case if the slice list\ncontains no proper slice).\n\nThe semantics for a slicing are as follows.  The primary must evaluate\nto a mapping object, and it is indexed (using the same\n``__getitem__()`` method as normal subscription) with a key that is\nconstructed from the slice list, as follows.  If the slice list\ncontains at least one comma, the key is a tuple containing the\nconversion of the slice items; otherwise, the conversion of the lone\nslice item is the key.  The conversion of a slice item that is an\nexpression is that expression.  The conversion of a proper slice is a\nslice object (see section *The standard type hierarchy*) whose\n``start``, ``stop`` and ``step`` attributes are the values of the\nexpressions given as lower bound, upper bound and stride,\nrespectively, substituting ``None`` for missing expressions.\n',
  'specialattrs': '\nSpecial Attributes\n******************\n\nThe implementation adds a few special read-only attributes to several\nobject types, where they are relevant.  Some of these are not reported\nby the ``dir()`` built-in function.\n\nobject.__dict__\n\n   A dictionary or other mapping object used to store an object\'s\n   (writable) attributes.\n\ninstance.__class__\n\n   The class to which a class instance belongs.\n\nclass.__bases__\n\n   The tuple of base classes of a class object.\n\nclass.__name__\n\n   The name of the class or type.\n\nclass.__qualname__\n\n   The *qualified name* of the class or type.\n\n   New in version 3.3.\n\nclass.__mro__\n\n   This attribute is a tuple of classes that are considered when\n   looking for base classes during method resolution.\n\nclass.mro()\n\n   This method can be overridden by a metaclass to customize the\n   method resolution order for its instances.  It is called at class\n   instantiation, and its result is stored in ``__mro__``.\n\nclass.__subclasses__()\n\n   Each class keeps a list of weak references to its immediate\n   subclasses.  This method returns a list of all those references\n   still alive. Example:\n\n      >>> int.__subclasses__()\n      [<class \'bool\'>]\n\n-[ Footnotes ]-\n\n[1] Additional information on these special methods may be found in\n    the Python Reference Manual (*Basic customization*).\n\n[2] As a consequence, the list ``[1, 2]`` is considered equal to\n    ``[1.0, 2.0]``, and similarly for tuples.\n\n[3] They must have since the parser can\'t tell the type of the\n    operands.\n\n[4] Cased characters are those with general category property being\n    one of "Lu" (Letter, uppercase), "Ll" (Letter, lowercase), or "Lt"\n    (Letter, titlecase).\n\n[5] To format only a tuple you should therefore provide a singleton\n    tuple whose only element is the tuple to be formatted.\n',
- 'specialnames': '\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators.  For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``type(x).__getitem__(x,\ni)``.  Except where mentioned, attempts to execute an operation raise\nan exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled.  For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense.  (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\nBasic customization\n===================\n\nobject.__new__(cls[, ...])\n\n   Called to create a new instance of class *cls*.  ``__new__()`` is a\n   static method (special-cased so you need not declare it as such)\n   that takes the class of which an instance was requested as its\n   first argument.  The remaining arguments are those passed to the\n   object constructor expression (the call to the class).  The return\n   value of ``__new__()`` should be the new object instance (usually\n   an instance of *cls*).\n\n   Typical implementations create a new instance of the class by\n   invoking the superclass\'s ``__new__()`` method using\n   ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n   arguments and then modifying the newly-created instance as\n   necessary before returning it.\n\n   If ``__new__()`` returns an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will be invoked like\n   ``__init__(self[, ...])``, where *self* is the new instance and the\n   remaining arguments are the same as were passed to ``__new__()``.\n\n   If ``__new__()`` does not return an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will not be invoked.\n\n   ``__new__()`` is intended mainly to allow subclasses of immutable\n   types (like int, str, or tuple) to customize instance creation.  It\n   is also commonly overridden in custom metaclasses in order to\n   customize class creation.\n\nobject.__init__(self[, ...])\n\n   Called when the instance is created.  The arguments are those\n   passed to the class constructor expression.  If a base class has an\n   ``__init__()`` method, the derived class\'s ``__init__()`` method,\n   if any, must explicitly call it to ensure proper initialization of\n   the base class part of the instance; for example:\n   ``BaseClass.__init__(self, [args...])``.  As a special constraint\n   on constructors, no value may be returned; doing so will cause a\n   ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n   Called when the instance is about to be destroyed.  This is also\n   called a destructor.  If a base class has a ``__del__()`` method,\n   the derived class\'s ``__del__()`` method, if any, must explicitly\n   call it to ensure proper deletion of the base class part of the\n   instance.  Note that it is possible (though not recommended!) for\n   the ``__del__()`` method to postpone destruction of the instance by\n   creating a new reference to it.  It may then be called at a later\n   time when this new reference is deleted.  It is not guaranteed that\n   ``__del__()`` methods are called for objects that still exist when\n   the interpreter exits.\n\n   Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n     decrements the reference count for ``x`` by one, and the latter\n     is only called when ``x``\'s reference count reaches zero.  Some\n     common situations that may prevent the reference count of an\n     object from going to zero include: circular references between\n     objects (e.g., a doubly-linked list or a tree data structure with\n     parent and child pointers); a reference to the object on the\n     stack frame of a function that caught an exception (the traceback\n     stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n     a reference to the object on the stack frame that raised an\n     unhandled exception in interactive mode (the traceback stored in\n     ``sys.last_traceback`` keeps the stack frame alive).  The first\n     situation can only be remedied by explicitly breaking the cycles;\n     the latter two situations can be resolved by storing ``None`` in\n     ``sys.last_traceback``. Circular references which are garbage are\n     detected when the option cycle detector is enabled (it\'s on by\n     default), but can only be cleaned up if there are no Python-\n     level ``__del__()`` methods involved. Refer to the documentation\n     for the ``gc`` module for more information about how\n     ``__del__()`` methods are handled by the cycle detector,\n     particularly the description of the ``garbage`` value.\n\n   Warning: Due to the precarious circumstances under which ``__del__()``\n     methods are invoked, exceptions that occur during their execution\n     are ignored, and a warning is printed to ``sys.stderr`` instead.\n     Also, when ``__del__()`` is invoked in response to a module being\n     deleted (e.g., when execution of the program is done), other\n     globals referenced by the ``__del__()`` method may already have\n     been deleted or in the process of being torn down (e.g. the\n     import machinery shutting down).  For this reason, ``__del__()``\n     methods should do the absolute minimum needed to maintain\n     external invariants.  Starting with version 1.5, Python\n     guarantees that globals whose name begins with a single\n     underscore are deleted from their module before other globals are\n     deleted; if no other references to such globals exist, this may\n     help in assuring that imported modules are still available at the\n     time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n   Called by the ``repr()`` built-in function to compute the\n   "official" string representation of an object.  If at all possible,\n   this should look like a valid Python expression that could be used\n   to recreate an object with the same value (given an appropriate\n   environment).  If this is not possible, a string of the form\n   ``<...some useful description...>`` should be returned. The return\n   value must be a string object. If a class defines ``__repr__()``\n   but not ``__str__()``, then ``__repr__()`` is also used when an\n   "informal" string representation of instances of that class is\n   required.\n\n   This is typically used for debugging, so it is important that the\n   representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n   Called by the ``str()`` built-in function and by the ``print()``\n   function to compute the "informal" string representation of an\n   object.  This differs from ``__repr__()`` in that it does not have\n   to be a valid Python expression: a more convenient or concise\n   representation may be used instead. The return value must be a\n   string object.\n\nobject.__bytes__(self)\n\n   Called by ``bytes()`` to compute a byte-string representation of an\n   object. This should return a ``bytes`` object.\n\nobject.__format__(self, format_spec)\n\n   Called by the ``format()`` built-in function (and by extension, the\n   ``format()`` method of class ``str``) to produce a "formatted"\n   string representation of an object. The ``format_spec`` argument is\n   a string that contains a description of the formatting options\n   desired. The interpretation of the ``format_spec`` argument is up\n   to the type implementing ``__format__()``, however most classes\n   will either delegate formatting to one of the built-in types, or\n   use a similar formatting option syntax.\n\n   See *Format Specification Mini-Language* for a description of the\n   standard formatting syntax.\n\n   The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n   These are the so-called "rich comparison" methods. The\n   correspondence between operator symbols and method names is as\n   follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n   ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n   ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n   ``x.__ge__(y)``.\n\n   A rich comparison method may return the singleton\n   ``NotImplemented`` if it does not implement the operation for a\n   given pair of arguments. By convention, ``False`` and ``True`` are\n   returned for a successful comparison. However, these methods can\n   return any value, so if the comparison operator is used in a\n   Boolean context (e.g., in the condition of an ``if`` statement),\n   Python will call ``bool()`` on the value to determine if the result\n   is true or false.\n\n   There are no implied relationships among the comparison operators.\n   The truth of ``x==y`` does not imply that ``x!=y`` is false.\n   Accordingly, when defining ``__eq__()``, one should also define\n   ``__ne__()`` so that the operators will behave as expected.  See\n   the paragraph on ``__hash__()`` for some important notes on\n   creating *hashable* objects which support custom comparison\n   operations and are usable as dictionary keys.\n\n   There are no swapped-argument versions of these methods (to be used\n   when the left argument does not support the operation but the right\n   argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n   other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n   reflection, and ``__eq__()`` and ``__ne__()`` are their own\n   reflection.\n\n   Arguments to rich comparison methods are never coerced.\n\n   To automatically generate ordering operations from a single root\n   operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n   Called by built-in function ``hash()`` and for operations on\n   members of hashed collections including ``set``, ``frozenset``, and\n   ``dict``.  ``__hash__()`` should return an integer.  The only\n   required property is that objects which compare equal have the same\n   hash value; it is advised to somehow mix together (e.g. using\n   exclusive or) the hash values for the components of the object that\n   also play a part in comparison of objects.\n\n   If a class does not define an ``__eq__()`` method it should not\n   define a ``__hash__()`` operation either; if it defines\n   ``__eq__()`` but not ``__hash__()``, its instances will not be\n   usable as items in hashable collections.  If a class defines\n   mutable objects and implements an ``__eq__()`` method, it should\n   not implement ``__hash__()``, since the implementation of hashable\n   collections requires that a key\'s hash value is immutable (if the\n   object\'s hash value changes, it will be in the wrong hash bucket).\n\n   User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n   by default; with them, all objects compare unequal (except with\n   themselves) and ``x.__hash__()`` returns an appropriate value such\n   that ``x == y`` implies both that ``x is y`` and ``hash(x) ==\n   hash(y)``.\n\n   Classes which inherit a ``__hash__()`` method from a parent class\n   but change the meaning of ``__eq__()`` such that the hash value\n   returned is no longer appropriate (e.g. by switching to a value-\n   based concept of equality instead of the default identity based\n   equality) can explicitly flag themselves as being unhashable by\n   setting ``__hash__ = None`` in the class definition. Doing so means\n   that not only will instances of the class raise an appropriate\n   ``TypeError`` when a program attempts to retrieve their hash value,\n   but they will also be correctly identified as unhashable when\n   checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n   which define their own ``__hash__()`` to explicitly raise\n   ``TypeError``).\n\n   If a class that overrides ``__eq__()`` needs to retain the\n   implementation of ``__hash__()`` from a parent class, the\n   interpreter must be told this explicitly by setting ``__hash__ =\n   <ParentClass>.__hash__``. Otherwise the inheritance of\n   ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n   explicitly set to ``None``.\n\n   Note: Note by default the ``__hash__()`` values of str, bytes and\n     datetime objects are "salted" with an unpredictable random value.\n     Although they remain constant within an individual Python\n     process, they are not predictable between repeated invocations of\n     Python.This is intended to provide protection against a denial-\n     of-service caused by carefully-chosen inputs that exploit the\n     worst case performance of a dict insertion, O(n^2) complexity.\n     See http://www.ocert.org/advisories/ocert-2011-003.html for\n     details.Changing hash values affects the order in which keys are\n     retrieved from a dict.  Note Python has never made guarantees\n     about this ordering (and it typically varies between 32-bit and\n     64-bit builds).See also ``PYTHONHASHSEED``.\n\n   Changed in version 3.3: Hash randomization is enabled by default.\n\nobject.__bool__(self)\n\n   Called to implement truth value testing and the built-in operation\n   ``bool()``; should return ``False`` or ``True``.  When this method\n   is not defined, ``__len__()`` is called, if it is defined, and the\n   object is considered true if its result is nonzero.  If a class\n   defines neither ``__len__()`` nor ``__bool__()``, all its instances\n   are considered true.\n\n\nCustomizing attribute access\n============================\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n   Called when an attribute lookup has not found the attribute in the\n   usual places (i.e. it is not an instance attribute nor is it found\n   in the class tree for ``self``).  ``name`` is the attribute name.\n   This method should return the (computed) attribute value or raise\n   an ``AttributeError`` exception.\n\n   Note that if the attribute is found through the normal mechanism,\n   ``__getattr__()`` is not called.  (This is an intentional asymmetry\n   between ``__getattr__()`` and ``__setattr__()``.) This is done both\n   for efficiency reasons and because otherwise ``__getattr__()``\n   would have no way to access other attributes of the instance.  Note\n   that at least for instance variables, you can fake total control by\n   not inserting any values in the instance attribute dictionary (but\n   instead inserting them in another object).  See the\n   ``__getattribute__()`` method below for a way to actually get total\n   control over attribute access.\n\nobject.__getattribute__(self, name)\n\n   Called unconditionally to implement attribute accesses for\n   instances of the class. If the class also defines\n   ``__getattr__()``, the latter will not be called unless\n   ``__getattribute__()`` either calls it explicitly or raises an\n   ``AttributeError``. This method should return the (computed)\n   attribute value or raise an ``AttributeError`` exception. In order\n   to avoid infinite recursion in this method, its implementation\n   should always call the base class method with the same name to\n   access any attributes it needs, for example,\n   ``object.__getattribute__(self, name)``.\n\n   Note: This method may still be bypassed when looking up special methods\n     as the result of implicit invocation via language syntax or\n     built-in functions. See *Special method lookup*.\n\nobject.__setattr__(self, name, value)\n\n   Called when an attribute assignment is attempted.  This is called\n   instead of the normal mechanism (i.e. store the value in the\n   instance dictionary). *name* is the attribute name, *value* is the\n   value to be assigned to it.\n\n   If ``__setattr__()`` wants to assign to an instance attribute, it\n   should call the base class method with the same name, for example,\n   ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n   Like ``__setattr__()`` but for attribute deletion instead of\n   assignment.  This should only be implemented if ``del obj.name`` is\n   meaningful for the object.\n\nobject.__dir__(self)\n\n   Called when ``dir()`` is called on the object. A sequence must be\n   returned. ``dir()`` converts the returned sequence to a list and\n   sorts it.\n\n\nImplementing Descriptors\n------------------------\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents).  In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' ``__dict__``.\n\nobject.__get__(self, instance, owner)\n\n   Called to get the attribute of the owner class (class attribute\n   access) or of an instance of that class (instance attribute\n   access). *owner* is always the owner class, while *instance* is the\n   instance that the attribute was accessed through, or ``None`` when\n   the attribute is accessed through the *owner*.  This method should\n   return the (computed) attribute value or raise an\n   ``AttributeError`` exception.\n\nobject.__set__(self, instance, value)\n\n   Called to set the attribute on an instance *instance* of the owner\n   class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n   Called to delete the attribute on an instance *instance* of the\n   owner class.\n\n\nInvoking Descriptors\n--------------------\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol:  ``__get__()``, ``__set__()``, and\n``__delete__()``. If any of those methods are defined for an object,\nit is said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, ``a.x`` has a\nlookup chain starting with ``a.__dict__[\'x\']``, then\n``type(a).__dict__[\'x\']``, and continuing through the base classes of\n``type(a)`` excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead.  Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called.\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the arguments are assembled depends on ``a``:\n\nDirect Call\n   The simplest and least common call is when user code directly\n   invokes a descriptor method:    ``x.__get__(a)``.\n\nInstance Binding\n   If binding to an object instance, ``a.x`` is transformed into the\n   call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n   If binding to a class, ``A.x`` is transformed into the call:\n   ``A.__dict__[\'x\'].__get__(None, A)``.\n\nSuper Binding\n   If ``a`` is an instance of ``super``, then the binding ``super(B,\n   obj).m()`` searches ``obj.__class__.__mro__`` for the base class\n   ``A`` immediately preceding ``B`` and then invokes the descriptor\n   with the call: ``A.__dict__[\'m\'].__get__(obj, obj.__class__)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined.  A descriptor can define\nany combination of ``__get__()``, ``__set__()`` and ``__delete__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary.  If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor.  Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method.  Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary.  In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented as non-data descriptors.  Accordingly, instances can\nredefine and override methods.  This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe ``property()`` function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n---------\n\nBy default, instances of classes have a dictionary for attribute\nstorage.  This wastes space for objects having very few instance\nvariables.  The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable.  Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__slots__\n\n   This class variable can be assigned a string, iterable, or sequence\n   of strings with variable names used by instances.  If defined in a\n   class, *__slots__* reserves space for the declared variables and\n   prevents the automatic creation of *__dict__* and *__weakref__* for\n   each instance.\n\n\nNotes on using *__slots__*\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n  attribute of that class will always be accessible, so a *__slots__*\n  definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n  variables not listed in the *__slots__* definition.  Attempts to\n  assign to an unlisted variable name raises ``AttributeError``. If\n  dynamic assignment of new variables is desired, then add\n  ``\'__dict__\'`` to the sequence of strings in the *__slots__*\n  declaration.\n\n* Without a *__weakref__* variable for each instance, classes defining\n  *__slots__* do not support weak references to its instances. If weak\n  reference support is needed, then add ``\'__weakref__\'`` to the\n  sequence of strings in the *__slots__* declaration.\n\n* *__slots__* are implemented at the class level by creating\n  descriptors (*Implementing Descriptors*) for each variable name.  As\n  a result, class attributes cannot be used to set default values for\n  instance variables defined by *__slots__*; otherwise, the class\n  attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n  where it is defined.  As a result, subclasses will have a *__dict__*\n  unless they also define *__slots__* (which must only contain names\n  of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the instance\n  variable defined by the base class slot is inaccessible (except by\n  retrieving its descriptor directly from the base class). This\n  renders the meaning of the program undefined.  In the future, a\n  check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n  "variable-length" built-in types such as ``int``, ``str`` and\n  ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n  also be used; however, in the future, special meaning may be\n  assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n  *__slots__*.\n\n\nCustomizing class creation\n==========================\n\nBy default, classes are constructed using ``type()``. The class body\nis executed in a new namespace and the class name is bound locally to\nthe result of ``type(name, bases, namespace)``.\n\nThe class creation process can be customised by passing the\n``metaclass`` keyword argument in the class definition line, or by\ninheriting from an existing class that included such an argument. In\nthe following example, both ``MyClass`` and ``MySubclass`` are\ninstances of ``Meta``:\n\n   class Meta(type):\n       pass\n\n   class MyClass(metaclass=Meta):\n       pass\n\n   class MySubclass(MyClass):\n       pass\n\nAny other keyword arguments that are specified in the class definition\nare passed through to all metaclass operations described below.\n\nWhen a class definition is executed, the following steps occur:\n\n* the appropriate metaclass is determined\n\n* the class namespace is prepared\n\n* the class body is executed\n\n* the class object is created\n\n\nDetermining the appropriate metaclass\n-------------------------------------\n\nThe appropriate metaclass for a class definition is determined as\nfollows:\n\n* if no bases and no explicit metaclass are given, then ``type()`` is\n  used\n\n* if an explicit metaclass is given and it is *not* an instance of\n  ``type()``, then it is used directly as the metaclass\n\n* if an instance of ``type()`` is given as the explicit metaclass, or\n  bases are defined, then the most derived metaclass is used\n\nThe most derived metaclass is selected from the explicitly specified\nmetaclass (if any) and the metaclasses (i.e. ``type(cls)``) of all\nspecified base classes. The most derived metaclass is one which is a\nsubtype of *all* of these candidate metaclasses. If none of the\ncandidate metaclasses meets that criterion, then the class definition\nwill fail with ``TypeError``.\n\n\nPreparing the class namespace\n-----------------------------\n\nOnce the appropriate metaclass has been identified, then the class\nnamespace is prepared. If the metaclass has a ``__prepare__``\nattribute, it is called as ``namespace = metaclass.__prepare__(name,\nbases, **kwds)`` (where the additional keyword arguments, if any, come\nfrom the class definition).\n\nIf the metaclass has no ``__prepare__`` attribute, then the class\nnamespace is initialised as an empty ``dict()`` instance.\n\nSee also:\n\n   **PEP 3115** - Metaclasses in Python 3000\n      Introduced the ``__prepare__`` namespace hook\n\n\nExecuting the class body\n------------------------\n\nThe class body is executed (approximately) as ``exec(body, globals(),\nnamespace)``. The key difference from a normal call to ``exec()`` is\nthat lexical scoping allows the class body (including any methods) to\nreference names from the current and outer scopes when the class\ndefinition occurs inside a function.\n\nHowever, even when the class definition occurs inside the function,\nmethods defined inside the class still cannot see names defined at the\nclass scope. Class variables must be accessed through the first\nparameter of instance or class methods, and cannot be accessed at all\nfrom static methods.\n\n\nCreating the class object\n-------------------------\n\nOnce the class namespace has been populated by executing the class\nbody, the class object is created by calling ``metaclass(name, bases,\nnamespace, **kwds)`` (the additional keywords passed here are the same\nas those passed to ``__prepare__``).\n\nThis class object is the one that will be referenced by the zero-\nargument form of ``super()``. ``__class__`` is an implicit closure\nreference created by the compiler if any methods in a class body refer\nto either ``__class__`` or ``super``. This allows the zero argument\nform of ``super()`` to correctly identify the class being defined\nbased on lexical scoping, while the class or instance that was used to\nmake the current call is identified based on the first argument passed\nto the method.\n\nAfter the class object is created, it is passed to the class\ndecorators included in the class definition (if any) and the resulting\nobject is bound in the local namespace as the defined class.\n\nSee also:\n\n   **PEP 3135** - New super\n      Describes the implicit ``__class__`` closure reference\n\n\nMetaclass example\n-----------------\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored include logging, interface checking, automatic\ndelegation, automatic property creation, proxies, frameworks, and\nautomatic resource locking/synchronization.\n\nHere is an example of a metaclass that uses an\n``collections.OrderedDict`` to remember the order that class members\nwere defined:\n\n   class OrderedClass(type):\n\n        @classmethod\n        def __prepare__(metacls, name, bases, **kwds):\n           return collections.OrderedDict()\n\n        def __new__(cls, name, bases, namespace, **kwds):\n           result = type.__new__(cls, name, bases, dict(namespace))\n           result.members = tuple(namespace)\n           return result\n\n   class A(metaclass=OrderedClass):\n       def one(self): pass\n       def two(self): pass\n       def three(self): pass\n       def four(self): pass\n\n   >>> A.members\n   (\'__module__\', \'one\', \'two\', \'three\', \'four\')\n\nWhen the class definition for *A* gets executed, the process begins\nwith calling the metaclass\'s ``__prepare__()`` method which returns an\nempty ``collections.OrderedDict``.  That mapping records the methods\nand attributes of *A* as they are defined within the body of the class\nstatement. Once those definitions are executed, the ordered dictionary\nis fully populated and the metaclass\'s ``__new__()`` method gets\ninvoked.  That method builds the new type and it saves the ordered\ndictionary keys in an attribute called ``members``.\n\n\nCustomizing instance and subclass checks\n========================================\n\nThe following methods are used to override the default behavior of the\n``isinstance()`` and ``issubclass()`` built-in functions.\n\nIn particular, the metaclass ``abc.ABCMeta`` implements these methods\nin order to allow the addition of Abstract Base Classes (ABCs) as\n"virtual base classes" to any class or type (including built-in\ntypes), including other ABCs.\n\nclass.__instancecheck__(self, instance)\n\n   Return true if *instance* should be considered a (direct or\n   indirect) instance of *class*. If defined, called to implement\n   ``isinstance(instance, class)``.\n\nclass.__subclasscheck__(self, subclass)\n\n   Return true if *subclass* should be considered a (direct or\n   indirect) subclass of *class*.  If defined, called to implement\n   ``issubclass(subclass, class)``.\n\nNote that these methods are looked up on the type (metaclass) of a\nclass.  They cannot be defined as class methods in the actual class.\nThis is consistent with the lookup of special methods that are called\non instances, only in this case the instance is itself a class.\n\nSee also:\n\n   **PEP 3119** - Introducing Abstract Base Classes\n      Includes the specification for customizing ``isinstance()`` and\n      ``issubclass()`` behavior through ``__instancecheck__()`` and\n      ``__subclasscheck__()``, with motivation for this functionality\n      in the context of adding Abstract Base Classes (see the ``abc``\n      module) to the language.\n\n\nEmulating callable objects\n==========================\n\nobject.__call__(self[, args...])\n\n   Called when the instance is "called" as a function; if this method\n   is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n   ``x.__call__(arg1, arg2, ...)``.\n\n\nEmulating container types\n=========================\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well.  The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items.  It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``get()``,\n``clear()``, ``setdefault()``, ``pop()``, ``popitem()``, ``copy()``,\nand ``update()`` behaving similar to those for Python\'s standard\ndictionary objects.  The ``collections`` module provides a\n``MutableMapping`` abstract base class to help create those methods\nfrom a base set of ``__getitem__()``, ``__setitem__()``,\n``__delitem__()``, and ``keys()``. Mutable sequences should provide\nmethods ``append()``, ``count()``, ``index()``, ``extend()``,\n``insert()``, ``pop()``, ``remove()``, ``reverse()`` and ``sort()``,\nlike Python standard list objects.  Finally, sequence types should\nimplement addition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods ``__add__()``, ``__radd__()``,\n``__iadd__()``, ``__mul__()``, ``__rmul__()`` and ``__imul__()``\ndescribed below; they should not define other numerical operators.  It\nis recommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should search the mapping\'s keys; for\nsequences, it should search through the values.  It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``keys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n   Called to implement the built-in function ``len()``.  Should return\n   the length of the object, an integer ``>=`` 0.  Also, an object\n   that doesn\'t define a ``__bool__()`` method and whose ``__len__()``\n   method returns zero is considered to be false in a Boolean context.\n\nNote: Slicing is done exclusively with the following three methods.  A\n  call like\n\n     a[1:2] = b\n\n  is translated to\n\n     a[slice(1, 2, None)] = b\n\n  and so forth.  Missing slice items are always filled in with\n  ``None``.\n\nobject.__getitem__(self, key)\n\n   Called to implement evaluation of ``self[key]``. For sequence\n   types, the accepted keys should be integers and slice objects.\n   Note that the special interpretation of negative indexes (if the\n   class wishes to emulate a sequence type) is up to the\n   ``__getitem__()`` method. If *key* is of an inappropriate type,\n   ``TypeError`` may be raised; if of a value outside the set of\n   indexes for the sequence (after any special interpretation of\n   negative values), ``IndexError`` should be raised. For mapping\n   types, if *key* is missing (not in the container), ``KeyError``\n   should be raised.\n\n   Note: ``for`` loops expect that an ``IndexError`` will be raised for\n     illegal indexes to allow proper detection of the end of the\n     sequence.\n\nobject.__setitem__(self, key, value)\n\n   Called to implement assignment to ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support changes to the values for keys, or if new keys\n   can be added, or for sequences if elements can be replaced.  The\n   same exceptions should be raised for improper *key* values as for\n   the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n   Called to implement deletion of ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support removal of keys, or for sequences if elements\n   can be removed from the sequence.  The same exceptions should be\n   raised for improper *key* values as for the ``__getitem__()``\n   method.\n\nobject.__iter__(self)\n\n   This method is called when an iterator is required for a container.\n   This method should return a new iterator object that can iterate\n   over all the objects in the container.  For mappings, it should\n   iterate over the keys of the container, and should also be made\n   available as the method ``keys()``.\n\n   Iterator objects also need to implement this method; they are\n   required to return themselves.  For more information on iterator\n   objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n   Called (if present) by the ``reversed()`` built-in to implement\n   reverse iteration.  It should return a new iterator object that\n   iterates over all the objects in the container in reverse order.\n\n   If the ``__reversed__()`` method is not provided, the\n   ``reversed()`` built-in will fall back to using the sequence\n   protocol (``__len__()`` and ``__getitem__()``).  Objects that\n   support the sequence protocol should only provide\n   ``__reversed__()`` if they can provide an implementation that is\n   more efficient than the one provided by ``reversed()``.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence.  However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n   Called to implement membership test operators.  Should return true\n   if *item* is in *self*, false otherwise.  For mapping objects, this\n   should consider the keys of the mapping rather than the values or\n   the key-item pairs.\n\n   For objects that don\'t define ``__contains__()``, the membership\n   test first tries iteration via ``__iter__()``, then the old\n   sequence iteration protocol via ``__getitem__()``, see *this\n   section in the language reference*.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__truediv__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n   ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n   ``|``).  For instance, to evaluate the expression ``x + y``, where\n   *x* is an instance of a class that has an ``__add__()`` method,\n   ``x.__add__(y)`` is called.  The ``__divmod__()`` method should be\n   the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n   should not be related to ``__truediv__()``.  Note that\n   ``__pow__()`` should be defined to accept an optional third\n   argument if the ternary version of the built-in ``pow()`` function\n   is to be supported.\n\n   If one of those methods does not support the operation with the\n   supplied arguments, it should return ``NotImplemented``.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n   ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n   ``|``) with reflected (swapped) operands. These functions are only\n   called if the left operand does not support the corresponding\n   operation and the operands are of different types. [2]  For\n   instance, to evaluate the expression ``x - y``, where *y* is an\n   instance of a class that has an ``__rsub__()`` method,\n   ``y.__rsub__(x)`` is called if ``x.__sub__(y)`` returns\n   *NotImplemented*.\n\n   Note that ternary ``pow()`` will not try calling ``__rpow__()``\n   (the coercion rules would become too complicated).\n\n   Note: If the right operand\'s type is a subclass of the left operand\'s\n     type and that subclass provides the reflected method for the\n     operation, this method will be called before the left operand\'s\n     non-reflected method.  This behavior allows subclasses to\n     override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n   These methods are called to implement the augmented arithmetic\n   assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n   ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``).  These methods\n   should attempt to do the operation in-place (modifying *self*) and\n   return the result (which could be, but does not have to be,\n   *self*).  If a specific method is not defined, the augmented\n   assignment falls back to the normal methods.  For instance, to\n   execute the statement ``x += y``, where *x* is an instance of a\n   class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n   called.  If *x* is an instance of a class that does not define a\n   ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n   considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n   Called to implement the unary arithmetic operations (``-``, ``+``,\n   ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__float__(self)\nobject.__round__(self[, n])\n\n   Called to implement the built-in functions ``complex()``,\n   ``int()``, ``float()`` and ``round()``.  Should return a value of\n   the appropriate type.\n\nobject.__index__(self)\n\n   Called to implement ``operator.index()``.  Also called whenever\n   Python needs an integer object (such as in slicing, or in the\n   built-in ``bin()``, ``hex()`` and ``oct()`` functions). Must return\n   an integer.\n\n\nWith Statement Context Managers\n===============================\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code.  Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n   Enter the runtime context related to this object. The ``with``\n   statement will bind this method\'s return value to the target(s)\n   specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n   Exit the runtime context related to this object. The parameters\n   describe the exception that caused the context to be exited. If the\n   context was exited without an exception, all three arguments will\n   be ``None``.\n\n   If an exception is supplied, and the method wishes to suppress the\n   exception (i.e., prevent it from being propagated), it should\n   return a true value. Otherwise, the exception will be processed\n   normally upon exit from this method.\n\n   Note that ``__exit__()`` methods should not reraise the passed-in\n   exception; this is the caller\'s responsibility.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n\n\nSpecial method lookup\n=====================\n\nFor custom classes, implicit invocations of special methods are only\nguaranteed to work correctly if defined on an object\'s type, not in\nthe object\'s instance dictionary.  That behaviour is the reason why\nthe following code raises an exception:\n\n   >>> class C:\n   ...     pass\n   ...\n   >>> c = C()\n   >>> c.__len__ = lambda: 5\n   >>> len(c)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: object of type \'C\' has no len()\n\nThe rationale behind this behaviour lies with a number of special\nmethods such as ``__hash__()`` and ``__repr__()`` that are implemented\nby all objects, including type objects. If the implicit lookup of\nthese methods used the conventional lookup process, they would fail\nwhen invoked on the type object itself:\n\n   >>> 1 .__hash__() == hash(1)\n   True\n   >>> int.__hash__() == hash(int)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: descriptor \'__hash__\' of \'int\' object needs an argument\n\nIncorrectly attempting to invoke an unbound method of a class in this\nway is sometimes referred to as \'metaclass confusion\', and is avoided\nby bypassing the instance when looking up special methods:\n\n   >>> type(1).__hash__(1) == hash(1)\n   True\n   >>> type(int).__hash__(int) == hash(int)\n   True\n\nIn addition to bypassing any instance attributes in the interest of\ncorrectness, implicit special method lookup generally also bypasses\nthe ``__getattribute__()`` method even of the object\'s metaclass:\n\n   >>> class Meta(type):\n   ...    def __getattribute__(*args):\n   ...       print("Metaclass getattribute invoked")\n   ...       return type.__getattribute__(*args)\n   ...\n   >>> class C(object, metaclass=Meta):\n   ...     def __len__(self):\n   ...         return 10\n   ...     def __getattribute__(*args):\n   ...         print("Class getattribute invoked")\n   ...         return object.__getattribute__(*args)\n   ...\n   >>> c = C()\n   >>> c.__len__()                 # Explicit lookup via instance\n   Class getattribute invoked\n   10\n   >>> type(c).__len__(c)          # Explicit lookup via type\n   Metaclass getattribute invoked\n   10\n   >>> len(c)                      # Implicit lookup\n   10\n\nBypassing the ``__getattribute__()`` machinery in this fashion\nprovides significant scope for speed optimisations within the\ninterpreter, at the cost of some flexibility in the handling of\nspecial methods (the special method *must* be set on the class object\nitself in order to be consistently invoked by the interpreter).\n\n-[ Footnotes ]-\n\n[1] It *is* possible in some cases to change an object\'s type, under\n    certain controlled conditions. It generally isn\'t a good idea\n    though, since it can lead to some very strange behaviour if it is\n    handled incorrectly.\n\n[2] For operands of the same type, it is assumed that if the non-\n    reflected method (such as ``__add__()``) fails the operation is\n    not supported, which is why the reflected method is not called.\n',
- 'string-methods': '\nString Methods\n**************\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n   Return a copy of the string with its first character capitalized\n   and the rest lowercased.\n\nstr.casefold()\n\n   Return a casefolded copy of the string. Casefolded strings may be\n   used for caseless matching.\n\n   Casefolding is similar to lowercasing but more aggressive because\n   it is intended to remove all case distinctions in a string. For\n   example, the German lowercase letter ``\'\xc3\x9f\'`` is equivalent to\n   ``"ss"``. Since it is already lowercase, ``lower()`` would do\n   nothing to ``\'\xc3\x9f\'``; ``casefold()`` converts it to ``"ss"``.\n\n   The casefolding algorithm is described in section 3.13 of the\n   Unicode Standard.\n\n   New in version 3.3.\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\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.encode(encoding="utf-8", errors="strict")\n\n   Return an encoded version of the string as a bytes object. Default\n   encoding is ``\'utf-8\'``. *errors* may be given to set a different\n   error handling scheme. The default for *errors* is ``\'strict\'``,\n   meaning that encoding errors raise a ``UnicodeError``. Other\n   possible values are ``\'ignore\'``, ``\'replace\'``,\n   ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n   registered via ``codecs.register_error()``, see section *Codec Base\n   Classes*. For a list of possible encodings, see section *Standard\n   Encodings*.\n\n   Changed in version 3.1: 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\nstr.expandtabs([tabsize])\n\n   Return a copy of the string where all tab characters are replaced\n   by zero or more spaces, depending on the current column and the\n   given tab size.  The column number is reset to zero after each\n   newline occurring in the string. If *tabsize* is not given, a tab\n   size of ``8`` characters is assumed.  This doesn\'t understand other\n   non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n   Return the lowest index in the string where substring *sub* is\n   found, such that *sub* is contained in the slice ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` if *sub* is not found.\n\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\nstr.format_map(mapping)\n\n   Similar to ``str.format(**mapping)``, except that ``mapping`` is\n   used directly and not copied to a ``dict`` .  This is useful if for\n   example ``mapping`` is a dict subclass:\n\n   >>> class Default(dict):\n   ...     def __missing__(self, key):\n   ...         return key\n   ...\n   >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n   \'Guido was born in country\'\n\n   New in version 3.2.\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.  A character\n   ``c`` is alphanumeric if one of the following returns ``True``:\n   ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n   ``c.isnumeric()``.\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.  Alphabetic\n   characters are those characters defined in the Unicode character\n   database as "Letter", i.e., those with general category property\n   being one of "Lm", "Lt", "Lu", "Ll", or "Lo".  Note that this is\n   different from the "Alphabetic" property defined in the Unicode\n   Standard.\n\nstr.isdecimal()\n\n   Return true if all characters in the string are decimal characters\n   and there is at least one character, false otherwise. Decimal\n   characters are those from general category "Nd". This category\n   includes digit characters, and all characters that can be used to\n   form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\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.  Digits include decimal\n   characters and digits that need special handling, such as the\n   compatibility superscript digits.  Formally, a digit is a character\n   that has the property value Numeric_Type=Digit or\n   Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n   Return true if the string is a valid identifier according to the\n   language definition, section *Identifiers and keywords*.\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\nstr.isnumeric()\n\n   Return true if all characters in the string are numeric characters,\n   and there is at least one character, false otherwise. Numeric\n   characters include digit characters, and all characters that have\n   the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n   ONE FIFTH.  Formally, numeric characters are those with the\n   property value Numeric_Type=Digit, Numeric_Type=Decimal or\n   Numeric_Type=Numeric.\n\nstr.isprintable()\n\n   Return true if all characters in the string are printable or the\n   string is empty, false otherwise.  Nonprintable characters are\n   those characters defined in the Unicode character database as\n   "Other" or "Separator", excepting the ASCII space (0x20) which is\n   considered printable.  (Note that printable characters in this\n   context are those which should not be escaped when ``repr()`` is\n   invoked on a string.  It has no bearing on the handling of strings\n   written to ``sys.stdout`` or ``sys.stderr``.)\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.  Whitespace\n   characters  are those characters defined in the Unicode character\n   database as "Other" or "Separator" and those with bidirectional\n   property being one of "WS", "B", or "S".\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\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\nstr.join(iterable)\n\n   Return a string which is the concatenation of the strings in the\n   *iterable* *iterable*.  A ``TypeError`` will be raised if there are\n   any non-string values in *iterable*, including ``bytes`` objects.\n   The separator between elements is the 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\nstr.lower()\n\n   Return a copy of the string with all the cased characters [4]\n   converted to lowercase.\n\n   The lowercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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\nstatic str.maketrans(x[, y[, z]])\n\n   This static method returns a translation table usable for\n   ``str.translate()``.\n\n   If there is only one argument, it must be a dictionary mapping\n   Unicode ordinals (integers) or characters (strings of length 1) to\n   Unicode ordinals, strings (of arbitrary lengths) or None.\n   Character keys will then be converted to ordinals.\n\n   If there are two arguments, they must be strings of equal length,\n   and in the resulting dictionary, each character in x will be mapped\n   to the character at the same position in y.  If there is a third\n   argument, it must be a string, whose characters will be mapped to\n   None in the result.\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\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\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\nstr.rsplit(sep=None, maxsplit=-1)\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\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\nstr.split(sep=None, maxsplit=-1)\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.  Line breaks are not included in the resulting list\n   unless *keepends* is given and true. This method uses the universal\n   newlines approach to splitting lines. Unlike ``split()``, if the\n   string ends with line boundary characters the returned list does\n   ``not`` have an empty last element.\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\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\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\nstr.swapcase()\n\n   Return a copy of the string with uppercase characters converted to\n   lowercase and vice versa. Note that it is not necessarily true that\n   ``s.swapcase().swapcase() == s``.\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\nstr.translate(map)\n\n   Return a copy of the *s* where all characters have been mapped\n   through the *map* which must be a dictionary of Unicode ordinals\n   (integers) to Unicode ordinals, strings or ``None``.  Unmapped\n   characters are left untouched. Characters mapped to ``None`` are\n   deleted.\n\n   You can use ``str.maketrans()`` to create a translation map from\n   character-to-character mappings in different formats.\n\n   Note: An even more flexible approach is to create a custom character\n     mapping codec using the ``codecs`` module (see\n     ``encodings.cp1251`` 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   The uppercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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',
+ 'specialnames': '\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators.  For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``type(x).__getitem__(x,\ni)``.  Except where mentioned, attempts to execute an operation raise\nan exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled.  For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense.  (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\nBasic customization\n===================\n\nobject.__new__(cls[, ...])\n\n   Called to create a new instance of class *cls*.  ``__new__()`` is a\n   static method (special-cased so you need not declare it as such)\n   that takes the class of which an instance was requested as its\n   first argument.  The remaining arguments are those passed to the\n   object constructor expression (the call to the class).  The return\n   value of ``__new__()`` should be the new object instance (usually\n   an instance of *cls*).\n\n   Typical implementations create a new instance of the class by\n   invoking the superclass\'s ``__new__()`` method using\n   ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n   arguments and then modifying the newly-created instance as\n   necessary before returning it.\n\n   If ``__new__()`` returns an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will be invoked like\n   ``__init__(self[, ...])``, where *self* is the new instance and the\n   remaining arguments are the same as were passed to ``__new__()``.\n\n   If ``__new__()`` does not return an instance of *cls*, then the new\n   instance\'s ``__init__()`` method will not be invoked.\n\n   ``__new__()`` is intended mainly to allow subclasses of immutable\n   types (like int, str, or tuple) to customize instance creation.  It\n   is also commonly overridden in custom metaclasses in order to\n   customize class creation.\n\nobject.__init__(self[, ...])\n\n   Called when the instance is created.  The arguments are those\n   passed to the class constructor expression.  If a base class has an\n   ``__init__()`` method, the derived class\'s ``__init__()`` method,\n   if any, must explicitly call it to ensure proper initialization of\n   the base class part of the instance; for example:\n   ``BaseClass.__init__(self, [args...])``.  As a special constraint\n   on constructors, no value may be returned; doing so will cause a\n   ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n   Called when the instance is about to be destroyed.  This is also\n   called a destructor.  If a base class has a ``__del__()`` method,\n   the derived class\'s ``__del__()`` method, if any, must explicitly\n   call it to ensure proper deletion of the base class part of the\n   instance.  Note that it is possible (though not recommended!) for\n   the ``__del__()`` method to postpone destruction of the instance by\n   creating a new reference to it.  It may then be called at a later\n   time when this new reference is deleted.  It is not guaranteed that\n   ``__del__()`` methods are called for objects that still exist when\n   the interpreter exits.\n\n   Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n     decrements the reference count for ``x`` by one, and the latter\n     is only called when ``x``\'s reference count reaches zero.  Some\n     common situations that may prevent the reference count of an\n     object from going to zero include: circular references between\n     objects (e.g., a doubly-linked list or a tree data structure with\n     parent and child pointers); a reference to the object on the\n     stack frame of a function that caught an exception (the traceback\n     stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n     a reference to the object on the stack frame that raised an\n     unhandled exception in interactive mode (the traceback stored in\n     ``sys.last_traceback`` keeps the stack frame alive).  The first\n     situation can only be remedied by explicitly breaking the cycles;\n     the latter two situations can be resolved by storing ``None`` in\n     ``sys.last_traceback``. Circular references which are garbage are\n     detected when the option cycle detector is enabled (it\'s on by\n     default), but can only be cleaned up if there are no Python-\n     level ``__del__()`` methods involved. Refer to the documentation\n     for the ``gc`` module for more information about how\n     ``__del__()`` methods are handled by the cycle detector,\n     particularly the description of the ``garbage`` value.\n\n   Warning: Due to the precarious circumstances under which ``__del__()``\n     methods are invoked, exceptions that occur during their execution\n     are ignored, and a warning is printed to ``sys.stderr`` instead.\n     Also, when ``__del__()`` is invoked in response to a module being\n     deleted (e.g., when execution of the program is done), other\n     globals referenced by the ``__del__()`` method may already have\n     been deleted or in the process of being torn down (e.g. the\n     import machinery shutting down).  For this reason, ``__del__()``\n     methods should do the absolute minimum needed to maintain\n     external invariants.  Starting with version 1.5, Python\n     guarantees that globals whose name begins with a single\n     underscore are deleted from their module before other globals are\n     deleted; if no other references to such globals exist, this may\n     help in assuring that imported modules are still available at the\n     time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n   Called by the ``repr()`` built-in function to compute the\n   "official" string representation of an object.  If at all possible,\n   this should look like a valid Python expression that could be used\n   to recreate an object with the same value (given an appropriate\n   environment).  If this is not possible, a string of the form\n   ``<...some useful description...>`` should be returned. The return\n   value must be a string object. If a class defines ``__repr__()``\n   but not ``__str__()``, then ``__repr__()`` is also used when an\n   "informal" string representation of instances of that class is\n   required.\n\n   This is typically used for debugging, so it is important that the\n   representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n   Called by the ``str()`` built-in function and by the ``print()``\n   function to compute the "informal" string representation of an\n   object.  This differs from ``__repr__()`` in that it does not have\n   to be a valid Python expression: a more convenient or concise\n   representation may be used instead. The return value must be a\n   string object.\n\nobject.__bytes__(self)\n\n   Called by ``bytes()`` to compute a byte-string representation of an\n   object. This should return a ``bytes`` object.\n\nobject.__format__(self, format_spec)\n\n   Called by the ``format()`` built-in function (and by extension, the\n   ``format()`` method of class ``str``) to produce a "formatted"\n   string representation of an object. The ``format_spec`` argument is\n   a string that contains a description of the formatting options\n   desired. The interpretation of the ``format_spec`` argument is up\n   to the type implementing ``__format__()``, however most classes\n   will either delegate formatting to one of the built-in types, or\n   use a similar formatting option syntax.\n\n   See *Format Specification Mini-Language* for a description of the\n   standard formatting syntax.\n\n   The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n   These are the so-called "rich comparison" methods. The\n   correspondence between operator symbols and method names is as\n   follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n   ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n   ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n   ``x.__ge__(y)``.\n\n   A rich comparison method may return the singleton\n   ``NotImplemented`` if it does not implement the operation for a\n   given pair of arguments. By convention, ``False`` and ``True`` are\n   returned for a successful comparison. However, these methods can\n   return any value, so if the comparison operator is used in a\n   Boolean context (e.g., in the condition of an ``if`` statement),\n   Python will call ``bool()`` on the value to determine if the result\n   is true or false.\n\n   There are no implied relationships among the comparison operators.\n   The truth of ``x==y`` does not imply that ``x!=y`` is false.\n   Accordingly, when defining ``__eq__()``, one should also define\n   ``__ne__()`` so that the operators will behave as expected.  See\n   the paragraph on ``__hash__()`` for some important notes on\n   creating *hashable* objects which support custom comparison\n   operations and are usable as dictionary keys.\n\n   There are no swapped-argument versions of these methods (to be used\n   when the left argument does not support the operation but the right\n   argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n   other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n   reflection, and ``__eq__()`` and ``__ne__()`` are their own\n   reflection.\n\n   Arguments to rich comparison methods are never coerced.\n\n   To automatically generate ordering operations from a single root\n   operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n   Called by built-in function ``hash()`` and for operations on\n   members of hashed collections including ``set``, ``frozenset``, and\n   ``dict``.  ``__hash__()`` should return an integer.  The only\n   required property is that objects which compare equal have the same\n   hash value; it is advised to somehow mix together (e.g. using\n   exclusive or) the hash values for the components of the object that\n   also play a part in comparison of objects.\n\n   If a class does not define an ``__eq__()`` method it should not\n   define a ``__hash__()`` operation either; if it defines\n   ``__eq__()`` but not ``__hash__()``, its instances will not be\n   usable as items in hashable collections.  If a class defines\n   mutable objects and implements an ``__eq__()`` method, it should\n   not implement ``__hash__()``, since the implementation of hashable\n   collections requires that a key\'s hash value is immutable (if the\n   object\'s hash value changes, it will be in the wrong hash bucket).\n\n   User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n   by default; with them, all objects compare unequal (except with\n   themselves) and ``x.__hash__()`` returns an appropriate value such\n   that ``x == y`` implies both that ``x is y`` and ``hash(x) ==\n   hash(y)``.\n\n   Classes which inherit a ``__hash__()`` method from a parent class\n   but change the meaning of ``__eq__()`` such that the hash value\n   returned is no longer appropriate (e.g. by switching to a value-\n   based concept of equality instead of the default identity based\n   equality) can explicitly flag themselves as being unhashable by\n   setting ``__hash__ = None`` in the class definition. Doing so means\n   that not only will instances of the class raise an appropriate\n   ``TypeError`` when a program attempts to retrieve their hash value,\n   but they will also be correctly identified as unhashable when\n   checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n   which define their own ``__hash__()`` to explicitly raise\n   ``TypeError``).\n\n   If a class that overrides ``__eq__()`` needs to retain the\n   implementation of ``__hash__()`` from a parent class, the\n   interpreter must be told this explicitly by setting ``__hash__ =\n   <ParentClass>.__hash__``. Otherwise the inheritance of\n   ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n   explicitly set to ``None``.\n\n   Note: By default, the ``__hash__()`` values of str, bytes and datetime\n     objects are "salted" with an unpredictable random value.\n     Although they remain constant within an individual Python\n     process, they are not predictable between repeated invocations of\n     Python.This is intended to provide protection against a denial-\n     of-service caused by carefully-chosen inputs that exploit the\n     worst case performance of a dict insertion, O(n^2) complexity.\n     See http://www.ocert.org/advisories/ocert-2011-003.html for\n     details.Changing hash values affects the iteration order of\n     dicts, sets and other mappings.  Python has never made guarantees\n     about this ordering (and it typically varies between 32-bit and\n     64-bit builds).See also ``PYTHONHASHSEED``.\n\n   Changed in version 3.3: Hash randomization is enabled by default.\n\nobject.__bool__(self)\n\n   Called to implement truth value testing and the built-in operation\n   ``bool()``; should return ``False`` or ``True``.  When this method\n   is not defined, ``__len__()`` is called, if it is defined, and the\n   object is considered true if its result is nonzero.  If a class\n   defines neither ``__len__()`` nor ``__bool__()``, all its instances\n   are considered true.\n\n\nCustomizing attribute access\n============================\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n   Called when an attribute lookup has not found the attribute in the\n   usual places (i.e. it is not an instance attribute nor is it found\n   in the class tree for ``self``).  ``name`` is the attribute name.\n   This method should return the (computed) attribute value or raise\n   an ``AttributeError`` exception.\n\n   Note that if the attribute is found through the normal mechanism,\n   ``__getattr__()`` is not called.  (This is an intentional asymmetry\n   between ``__getattr__()`` and ``__setattr__()``.) This is done both\n   for efficiency reasons and because otherwise ``__getattr__()``\n   would have no way to access other attributes of the instance.  Note\n   that at least for instance variables, you can fake total control by\n   not inserting any values in the instance attribute dictionary (but\n   instead inserting them in another object).  See the\n   ``__getattribute__()`` method below for a way to actually get total\n   control over attribute access.\n\nobject.__getattribute__(self, name)\n\n   Called unconditionally to implement attribute accesses for\n   instances of the class. If the class also defines\n   ``__getattr__()``, the latter will not be called unless\n   ``__getattribute__()`` either calls it explicitly or raises an\n   ``AttributeError``. This method should return the (computed)\n   attribute value or raise an ``AttributeError`` exception. In order\n   to avoid infinite recursion in this method, its implementation\n   should always call the base class method with the same name to\n   access any attributes it needs, for example,\n   ``object.__getattribute__(self, name)``.\n\n   Note: This method may still be bypassed when looking up special methods\n     as the result of implicit invocation via language syntax or\n     built-in functions. See *Special method lookup*.\n\nobject.__setattr__(self, name, value)\n\n   Called when an attribute assignment is attempted.  This is called\n   instead of the normal mechanism (i.e. store the value in the\n   instance dictionary). *name* is the attribute name, *value* is the\n   value to be assigned to it.\n\n   If ``__setattr__()`` wants to assign to an instance attribute, it\n   should call the base class method with the same name, for example,\n   ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n   Like ``__setattr__()`` but for attribute deletion instead of\n   assignment.  This should only be implemented if ``del obj.name`` is\n   meaningful for the object.\n\nobject.__dir__(self)\n\n   Called when ``dir()`` is called on the object. A sequence must be\n   returned. ``dir()`` converts the returned sequence to a list and\n   sorts it.\n\n\nImplementing Descriptors\n------------------------\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents).  In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' ``__dict__``.\n\nobject.__get__(self, instance, owner)\n\n   Called to get the attribute of the owner class (class attribute\n   access) or of an instance of that class (instance attribute\n   access). *owner* is always the owner class, while *instance* is the\n   instance that the attribute was accessed through, or ``None`` when\n   the attribute is accessed through the *owner*.  This method should\n   return the (computed) attribute value or raise an\n   ``AttributeError`` exception.\n\nobject.__set__(self, instance, value)\n\n   Called to set the attribute on an instance *instance* of the owner\n   class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n   Called to delete the attribute on an instance *instance* of the\n   owner class.\n\n\nInvoking Descriptors\n--------------------\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol:  ``__get__()``, ``__set__()``, and\n``__delete__()``. If any of those methods are defined for an object,\nit is said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, ``a.x`` has a\nlookup chain starting with ``a.__dict__[\'x\']``, then\n``type(a).__dict__[\'x\']``, and continuing through the base classes of\n``type(a)`` excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead.  Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called.\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the arguments are assembled depends on ``a``:\n\nDirect Call\n   The simplest and least common call is when user code directly\n   invokes a descriptor method:    ``x.__get__(a)``.\n\nInstance Binding\n   If binding to an object instance, ``a.x`` is transformed into the\n   call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n   If binding to a class, ``A.x`` is transformed into the call:\n   ``A.__dict__[\'x\'].__get__(None, A)``.\n\nSuper Binding\n   If ``a`` is an instance of ``super``, then the binding ``super(B,\n   obj).m()`` searches ``obj.__class__.__mro__`` for the base class\n   ``A`` immediately preceding ``B`` and then invokes the descriptor\n   with the call: ``A.__dict__[\'m\'].__get__(obj, obj.__class__)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined.  A descriptor can define\nany combination of ``__get__()``, ``__set__()`` and ``__delete__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary.  If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor.  Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method.  Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary.  In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented as non-data descriptors.  Accordingly, instances can\nredefine and override methods.  This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe ``property()`` function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n---------\n\nBy default, instances of classes have a dictionary for attribute\nstorage.  This wastes space for objects having very few instance\nvariables.  The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable.  Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__slots__\n\n   This class variable can be assigned a string, iterable, or sequence\n   of strings with variable names used by instances.  If defined in a\n   class, *__slots__* reserves space for the declared variables and\n   prevents the automatic creation of *__dict__* and *__weakref__* for\n   each instance.\n\n\nNotes on using *__slots__*\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n  attribute of that class will always be accessible, so a *__slots__*\n  definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n  variables not listed in the *__slots__* definition.  Attempts to\n  assign to an unlisted variable name raises ``AttributeError``. If\n  dynamic assignment of new variables is desired, then add\n  ``\'__dict__\'`` to the sequence of strings in the *__slots__*\n  declaration.\n\n* Without a *__weakref__* variable for each instance, classes defining\n  *__slots__* do not support weak references to its instances. If weak\n  reference support is needed, then add ``\'__weakref__\'`` to the\n  sequence of strings in the *__slots__* declaration.\n\n* *__slots__* are implemented at the class level by creating\n  descriptors (*Implementing Descriptors*) for each variable name.  As\n  a result, class attributes cannot be used to set default values for\n  instance variables defined by *__slots__*; otherwise, the class\n  attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n  where it is defined.  As a result, subclasses will have a *__dict__*\n  unless they also define *__slots__* (which must only contain names\n  of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the instance\n  variable defined by the base class slot is inaccessible (except by\n  retrieving its descriptor directly from the base class). This\n  renders the meaning of the program undefined.  In the future, a\n  check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n  "variable-length" built-in types such as ``int``, ``str`` and\n  ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n  also be used; however, in the future, special meaning may be\n  assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n  *__slots__*.\n\n\nCustomizing class creation\n==========================\n\nBy default, classes are constructed using ``type()``. The class body\nis executed in a new namespace and the class name is bound locally to\nthe result of ``type(name, bases, namespace)``.\n\nThe class creation process can be customised by passing the\n``metaclass`` keyword argument in the class definition line, or by\ninheriting from an existing class that included such an argument. In\nthe following example, both ``MyClass`` and ``MySubclass`` are\ninstances of ``Meta``:\n\n   class Meta(type):\n       pass\n\n   class MyClass(metaclass=Meta):\n       pass\n\n   class MySubclass(MyClass):\n       pass\n\nAny other keyword arguments that are specified in the class definition\nare passed through to all metaclass operations described below.\n\nWhen a class definition is executed, the following steps occur:\n\n* the appropriate metaclass is determined\n\n* the class namespace is prepared\n\n* the class body is executed\n\n* the class object is created\n\n\nDetermining the appropriate metaclass\n-------------------------------------\n\nThe appropriate metaclass for a class definition is determined as\nfollows:\n\n* if no bases and no explicit metaclass are given, then ``type()`` is\n  used\n\n* if an explicit metaclass is given and it is *not* an instance of\n  ``type()``, then it is used directly as the metaclass\n\n* if an instance of ``type()`` is given as the explicit metaclass, or\n  bases are defined, then the most derived metaclass is used\n\nThe most derived metaclass is selected from the explicitly specified\nmetaclass (if any) and the metaclasses (i.e. ``type(cls)``) of all\nspecified base classes. The most derived metaclass is one which is a\nsubtype of *all* of these candidate metaclasses. If none of the\ncandidate metaclasses meets that criterion, then the class definition\nwill fail with ``TypeError``.\n\n\nPreparing the class namespace\n-----------------------------\n\nOnce the appropriate metaclass has been identified, then the class\nnamespace is prepared. If the metaclass has a ``__prepare__``\nattribute, it is called as ``namespace = metaclass.__prepare__(name,\nbases, **kwds)`` (where the additional keyword arguments, if any, come\nfrom the class definition).\n\nIf the metaclass has no ``__prepare__`` attribute, then the class\nnamespace is initialised as an empty ``dict()`` instance.\n\nSee also:\n\n   **PEP 3115** - Metaclasses in Python 3000\n      Introduced the ``__prepare__`` namespace hook\n\n\nExecuting the class body\n------------------------\n\nThe class body is executed (approximately) as ``exec(body, globals(),\nnamespace)``. The key difference from a normal call to ``exec()`` is\nthat lexical scoping allows the class body (including any methods) to\nreference names from the current and outer scopes when the class\ndefinition occurs inside a function.\n\nHowever, even when the class definition occurs inside the function,\nmethods defined inside the class still cannot see names defined at the\nclass scope. Class variables must be accessed through the first\nparameter of instance or class methods, and cannot be accessed at all\nfrom static methods.\n\n\nCreating the class object\n-------------------------\n\nOnce the class namespace has been populated by executing the class\nbody, the class object is created by calling ``metaclass(name, bases,\nnamespace, **kwds)`` (the additional keywords passed here are the same\nas those passed to ``__prepare__``).\n\nThis class object is the one that will be referenced by the zero-\nargument form of ``super()``. ``__class__`` is an implicit closure\nreference created by the compiler if any methods in a class body refer\nto either ``__class__`` or ``super``. This allows the zero argument\nform of ``super()`` to correctly identify the class being defined\nbased on lexical scoping, while the class or instance that was used to\nmake the current call is identified based on the first argument passed\nto the method.\n\nAfter the class object is created, it is passed to the class\ndecorators included in the class definition (if any) and the resulting\nobject is bound in the local namespace as the defined class.\n\nSee also:\n\n   **PEP 3135** - New super\n      Describes the implicit ``__class__`` closure reference\n\n\nMetaclass example\n-----------------\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored include logging, interface checking, automatic\ndelegation, automatic property creation, proxies, frameworks, and\nautomatic resource locking/synchronization.\n\nHere is an example of a metaclass that uses an\n``collections.OrderedDict`` to remember the order that class members\nwere defined:\n\n   class OrderedClass(type):\n\n        @classmethod\n        def __prepare__(metacls, name, bases, **kwds):\n           return collections.OrderedDict()\n\n        def __new__(cls, name, bases, namespace, **kwds):\n           result = type.__new__(cls, name, bases, dict(namespace))\n           result.members = tuple(namespace)\n           return result\n\n   class A(metaclass=OrderedClass):\n       def one(self): pass\n       def two(self): pass\n       def three(self): pass\n       def four(self): pass\n\n   >>> A.members\n   (\'__module__\', \'one\', \'two\', \'three\', \'four\')\n\nWhen the class definition for *A* gets executed, the process begins\nwith calling the metaclass\'s ``__prepare__()`` method which returns an\nempty ``collections.OrderedDict``.  That mapping records the methods\nand attributes of *A* as they are defined within the body of the class\nstatement. Once those definitions are executed, the ordered dictionary\nis fully populated and the metaclass\'s ``__new__()`` method gets\ninvoked.  That method builds the new type and it saves the ordered\ndictionary keys in an attribute called ``members``.\n\n\nCustomizing instance and subclass checks\n========================================\n\nThe following methods are used to override the default behavior of the\n``isinstance()`` and ``issubclass()`` built-in functions.\n\nIn particular, the metaclass ``abc.ABCMeta`` implements these methods\nin order to allow the addition of Abstract Base Classes (ABCs) as\n"virtual base classes" to any class or type (including built-in\ntypes), including other ABCs.\n\nclass.__instancecheck__(self, instance)\n\n   Return true if *instance* should be considered a (direct or\n   indirect) instance of *class*. If defined, called to implement\n   ``isinstance(instance, class)``.\n\nclass.__subclasscheck__(self, subclass)\n\n   Return true if *subclass* should be considered a (direct or\n   indirect) subclass of *class*.  If defined, called to implement\n   ``issubclass(subclass, class)``.\n\nNote that these methods are looked up on the type (metaclass) of a\nclass.  They cannot be defined as class methods in the actual class.\nThis is consistent with the lookup of special methods that are called\non instances, only in this case the instance is itself a class.\n\nSee also:\n\n   **PEP 3119** - Introducing Abstract Base Classes\n      Includes the specification for customizing ``isinstance()`` and\n      ``issubclass()`` behavior through ``__instancecheck__()`` and\n      ``__subclasscheck__()``, with motivation for this functionality\n      in the context of adding Abstract Base Classes (see the ``abc``\n      module) to the language.\n\n\nEmulating callable objects\n==========================\n\nobject.__call__(self[, args...])\n\n   Called when the instance is "called" as a function; if this method\n   is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n   ``x.__call__(arg1, arg2, ...)``.\n\n\nEmulating container types\n=========================\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well.  The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items.  It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``get()``,\n``clear()``, ``setdefault()``, ``pop()``, ``popitem()``, ``copy()``,\nand ``update()`` behaving similar to those for Python\'s standard\ndictionary objects.  The ``collections`` module provides a\n``MutableMapping`` abstract base class to help create those methods\nfrom a base set of ``__getitem__()``, ``__setitem__()``,\n``__delitem__()``, and ``keys()``. Mutable sequences should provide\nmethods ``append()``, ``count()``, ``index()``, ``extend()``,\n``insert()``, ``pop()``, ``remove()``, ``reverse()`` and ``sort()``,\nlike Python standard list objects.  Finally, sequence types should\nimplement addition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods ``__add__()``, ``__radd__()``,\n``__iadd__()``, ``__mul__()``, ``__rmul__()`` and ``__imul__()``\ndescribed below; they should not define other numerical operators.  It\nis recommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should search the mapping\'s keys; for\nsequences, it should search through the values.  It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``keys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n   Called to implement the built-in function ``len()``.  Should return\n   the length of the object, an integer ``>=`` 0.  Also, an object\n   that doesn\'t define a ``__bool__()`` method and whose ``__len__()``\n   method returns zero is considered to be false in a Boolean context.\n\nNote: Slicing is done exclusively with the following three methods.  A\n  call like\n\n     a[1:2] = b\n\n  is translated to\n\n     a[slice(1, 2, None)] = b\n\n  and so forth.  Missing slice items are always filled in with\n  ``None``.\n\nobject.__getitem__(self, key)\n\n   Called to implement evaluation of ``self[key]``. For sequence\n   types, the accepted keys should be integers and slice objects.\n   Note that the special interpretation of negative indexes (if the\n   class wishes to emulate a sequence type) is up to the\n   ``__getitem__()`` method. If *key* is of an inappropriate type,\n   ``TypeError`` may be raised; if of a value outside the set of\n   indexes for the sequence (after any special interpretation of\n   negative values), ``IndexError`` should be raised. For mapping\n   types, if *key* is missing (not in the container), ``KeyError``\n   should be raised.\n\n   Note: ``for`` loops expect that an ``IndexError`` will be raised for\n     illegal indexes to allow proper detection of the end of the\n     sequence.\n\nobject.__setitem__(self, key, value)\n\n   Called to implement assignment to ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support changes to the values for keys, or if new keys\n   can be added, or for sequences if elements can be replaced.  The\n   same exceptions should be raised for improper *key* values as for\n   the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n   Called to implement deletion of ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support removal of keys, or for sequences if elements\n   can be removed from the sequence.  The same exceptions should be\n   raised for improper *key* values as for the ``__getitem__()``\n   method.\n\nobject.__iter__(self)\n\n   This method is called when an iterator is required for a container.\n   This method should return a new iterator object that can iterate\n   over all the objects in the container.  For mappings, it should\n   iterate over the keys of the container, and should also be made\n   available as the method ``keys()``.\n\n   Iterator objects also need to implement this method; they are\n   required to return themselves.  For more information on iterator\n   objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n   Called (if present) by the ``reversed()`` built-in to implement\n   reverse iteration.  It should return a new iterator object that\n   iterates over all the objects in the container in reverse order.\n\n   If the ``__reversed__()`` method is not provided, the\n   ``reversed()`` built-in will fall back to using the sequence\n   protocol (``__len__()`` and ``__getitem__()``).  Objects that\n   support the sequence protocol should only provide\n   ``__reversed__()`` if they can provide an implementation that is\n   more efficient than the one provided by ``reversed()``.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence.  However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n   Called to implement membership test operators.  Should return true\n   if *item* is in *self*, false otherwise.  For mapping objects, this\n   should consider the keys of the mapping rather than the values or\n   the key-item pairs.\n\n   For objects that don\'t define ``__contains__()``, the membership\n   test first tries iteration via ``__iter__()``, then the old\n   sequence iteration protocol via ``__getitem__()``, see *this\n   section in the language reference*.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__truediv__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n   ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n   ``|``).  For instance, to evaluate the expression ``x + y``, where\n   *x* is an instance of a class that has an ``__add__()`` method,\n   ``x.__add__(y)`` is called.  The ``__divmod__()`` method should be\n   the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n   should not be related to ``__truediv__()``.  Note that\n   ``__pow__()`` should be defined to accept an optional third\n   argument if the ternary version of the built-in ``pow()`` function\n   is to be supported.\n\n   If one of those methods does not support the operation with the\n   supplied arguments, it should return ``NotImplemented``.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n   ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n   ``|``) with reflected (swapped) operands. These functions are only\n   called if the left operand does not support the corresponding\n   operation and the operands are of different types. [2]  For\n   instance, to evaluate the expression ``x - y``, where *y* is an\n   instance of a class that has an ``__rsub__()`` method,\n   ``y.__rsub__(x)`` is called if ``x.__sub__(y)`` returns\n   *NotImplemented*.\n\n   Note that ternary ``pow()`` will not try calling ``__rpow__()``\n   (the coercion rules would become too complicated).\n\n   Note: If the right operand\'s type is a subclass of the left operand\'s\n     type and that subclass provides the reflected method for the\n     operation, this method will be called before the left operand\'s\n     non-reflected method.  This behavior allows subclasses to\n     override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n   These methods are called to implement the augmented arithmetic\n   assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n   ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``).  These methods\n   should attempt to do the operation in-place (modifying *self*) and\n   return the result (which could be, but does not have to be,\n   *self*).  If a specific method is not defined, the augmented\n   assignment falls back to the normal methods.  For instance, to\n   execute the statement ``x += y``, where *x* is an instance of a\n   class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n   called.  If *x* is an instance of a class that does not define a\n   ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n   considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n   Called to implement the unary arithmetic operations (``-``, ``+``,\n   ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__float__(self)\nobject.__round__(self[, n])\n\n   Called to implement the built-in functions ``complex()``,\n   ``int()``, ``float()`` and ``round()``.  Should return a value of\n   the appropriate type.\n\nobject.__index__(self)\n\n   Called to implement ``operator.index()``.  Also called whenever\n   Python needs an integer object (such as in slicing, or in the\n   built-in ``bin()``, ``hex()`` and ``oct()`` functions). Must return\n   an integer.\n\n\nWith Statement Context Managers\n===============================\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code.  Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n   Enter the runtime context related to this object. The ``with``\n   statement will bind this method\'s return value to the target(s)\n   specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n   Exit the runtime context related to this object. The parameters\n   describe the exception that caused the context to be exited. If the\n   context was exited without an exception, all three arguments will\n   be ``None``.\n\n   If an exception is supplied, and the method wishes to suppress the\n   exception (i.e., prevent it from being propagated), it should\n   return a true value. Otherwise, the exception will be processed\n   normally upon exit from this method.\n\n   Note that ``__exit__()`` methods should not reraise the passed-in\n   exception; this is the caller\'s responsibility.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n\n\nSpecial method lookup\n=====================\n\nFor custom classes, implicit invocations of special methods are only\nguaranteed to work correctly if defined on an object\'s type, not in\nthe object\'s instance dictionary.  That behaviour is the reason why\nthe following code raises an exception:\n\n   >>> class C:\n   ...     pass\n   ...\n   >>> c = C()\n   >>> c.__len__ = lambda: 5\n   >>> len(c)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: object of type \'C\' has no len()\n\nThe rationale behind this behaviour lies with a number of special\nmethods such as ``__hash__()`` and ``__repr__()`` that are implemented\nby all objects, including type objects. If the implicit lookup of\nthese methods used the conventional lookup process, they would fail\nwhen invoked on the type object itself:\n\n   >>> 1 .__hash__() == hash(1)\n   True\n   >>> int.__hash__() == hash(int)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: descriptor \'__hash__\' of \'int\' object needs an argument\n\nIncorrectly attempting to invoke an unbound method of a class in this\nway is sometimes referred to as \'metaclass confusion\', and is avoided\nby bypassing the instance when looking up special methods:\n\n   >>> type(1).__hash__(1) == hash(1)\n   True\n   >>> type(int).__hash__(int) == hash(int)\n   True\n\nIn addition to bypassing any instance attributes in the interest of\ncorrectness, implicit special method lookup generally also bypasses\nthe ``__getattribute__()`` method even of the object\'s metaclass:\n\n   >>> class Meta(type):\n   ...    def __getattribute__(*args):\n   ...       print("Metaclass getattribute invoked")\n   ...       return type.__getattribute__(*args)\n   ...\n   >>> class C(object, metaclass=Meta):\n   ...     def __len__(self):\n   ...         return 10\n   ...     def __getattribute__(*args):\n   ...         print("Class getattribute invoked")\n   ...         return object.__getattribute__(*args)\n   ...\n   >>> c = C()\n   >>> c.__len__()                 # Explicit lookup via instance\n   Class getattribute invoked\n   10\n   >>> type(c).__len__(c)          # Explicit lookup via type\n   Metaclass getattribute invoked\n   10\n   >>> len(c)                      # Implicit lookup\n   10\n\nBypassing the ``__getattribute__()`` machinery in this fashion\nprovides significant scope for speed optimisations within the\ninterpreter, at the cost of some flexibility in the handling of\nspecial methods (the special method *must* be set on the class object\nitself in order to be consistently invoked by the interpreter).\n\n-[ Footnotes ]-\n\n[1] It *is* possible in some cases to change an object\'s type, under\n    certain controlled conditions. It generally isn\'t a good idea\n    though, since it can lead to some very strange behaviour if it is\n    handled incorrectly.\n\n[2] For operands of the same type, it is assumed that if the non-\n    reflected method (such as ``__add__()``) fails the operation is\n    not supported, which is why the reflected method is not called.\n',
+ 'string-methods': '\nString Methods\n**************\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n   Return a copy of the string with its first character capitalized\n   and the rest lowercased.\n\nstr.casefold()\n\n   Return a casefolded copy of the string. Casefolded strings may be\n   used for caseless matching.\n\n   Casefolding is similar to lowercasing but more aggressive because\n   it is intended to remove all case distinctions in a string. For\n   example, the German lowercase letter ``\'\xc3\x9f\'`` is equivalent to\n   ``"ss"``. Since it is already lowercase, ``lower()`` would do\n   nothing to ``\'\xc3\x9f\'``; ``casefold()`` converts it to ``"ss"``.\n\n   The casefolding algorithm is described in section 3.13 of the\n   Unicode Standard.\n\n   New in version 3.3.\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\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.encode(encoding="utf-8", errors="strict")\n\n   Return an encoded version of the string as a bytes object. Default\n   encoding is ``\'utf-8\'``. *errors* may be given to set a different\n   error handling scheme. The default for *errors* is ``\'strict\'``,\n   meaning that encoding errors raise a ``UnicodeError``. Other\n   possible values are ``\'ignore\'``, ``\'replace\'``,\n   ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n   registered via ``codecs.register_error()``, see section *Codec Base\n   Classes*. For a list of possible encodings, see section *Standard\n   Encodings*.\n\n   Changed in version 3.1: 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\nstr.expandtabs([tabsize])\n\n   Return a copy of the string where all tab characters are replaced\n   by zero or more spaces, depending on the current column and the\n   given tab size.  The column number is reset to zero after each\n   newline occurring in the string. If *tabsize* is not given, a tab\n   size of ``8`` characters is assumed.  This doesn\'t understand other\n   non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n   Return the lowest index in the string where substring *sub* is\n   found, such that *sub* is contained in the slice ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` if *sub* is not found.\n\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\nstr.format_map(mapping)\n\n   Similar to ``str.format(**mapping)``, except that ``mapping`` is\n   used directly and not copied to a ``dict`` .  This is useful if for\n   example ``mapping`` is a dict subclass:\n\n   >>> class Default(dict):\n   ...     def __missing__(self, key):\n   ...         return key\n   ...\n   >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n   \'Guido was born in country\'\n\n   New in version 3.2.\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.  A character\n   ``c`` is alphanumeric if one of the following returns ``True``:\n   ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n   ``c.isnumeric()``.\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.  Alphabetic\n   characters are those characters defined in the Unicode character\n   database as "Letter", i.e., those with general category property\n   being one of "Lm", "Lt", "Lu", "Ll", or "Lo".  Note that this is\n   different from the "Alphabetic" property defined in the Unicode\n   Standard.\n\nstr.isdecimal()\n\n   Return true if all characters in the string are decimal characters\n   and there is at least one character, false otherwise. Decimal\n   characters are those from general category "Nd". This category\n   includes digit characters, and all characters that can be used to\n   form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\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.  Digits include decimal\n   characters and digits that need special handling, such as the\n   compatibility superscript digits.  Formally, a digit is a character\n   that has the property value Numeric_Type=Digit or\n   Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n   Return true if the string is a valid identifier according to the\n   language definition, section *Identifiers and keywords*.\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\nstr.isnumeric()\n\n   Return true if all characters in the string are numeric characters,\n   and there is at least one character, false otherwise. Numeric\n   characters include digit characters, and all characters that have\n   the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n   ONE FIFTH.  Formally, numeric characters are those with the\n   property value Numeric_Type=Digit, Numeric_Type=Decimal or\n   Numeric_Type=Numeric.\n\nstr.isprintable()\n\n   Return true if all characters in the string are printable or the\n   string is empty, false otherwise.  Nonprintable characters are\n   those characters defined in the Unicode character database as\n   "Other" or "Separator", excepting the ASCII space (0x20) which is\n   considered printable.  (Note that printable characters in this\n   context are those which should not be escaped when ``repr()`` is\n   invoked on a string.  It has no bearing on the handling of strings\n   written to ``sys.stdout`` or ``sys.stderr``.)\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.  Whitespace\n   characters  are those characters defined in the Unicode character\n   database as "Other" or "Separator" and those with bidirectional\n   property being one of "WS", "B", or "S".\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\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\nstr.join(iterable)\n\n   Return a string which is the concatenation of the strings in the\n   *iterable* *iterable*.  A ``TypeError`` will be raised if there are\n   any non-string values in *iterable*, including ``bytes`` objects.\n   The separator between elements is the 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\nstr.lower()\n\n   Return a copy of the string with all the cased characters [4]\n   converted to lowercase.\n\n   The lowercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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\nstatic str.maketrans(x[, y[, z]])\n\n   This static method returns a translation table usable for\n   ``str.translate()``.\n\n   If there is only one argument, it must be a dictionary mapping\n   Unicode ordinals (integers) or characters (strings of length 1) to\n   Unicode ordinals, strings (of arbitrary lengths) or None.\n   Character keys will then be converted to ordinals.\n\n   If there are two arguments, they must be strings of equal length,\n   and in the resulting dictionary, each character in x will be mapped\n   to the character at the same position in y.  If there is a third\n   argument, it must be a string, whose characters will be mapped to\n   None in the result.\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\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\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\nstr.rsplit(sep=None, maxsplit=-1)\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\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\nstr.split(sep=None, maxsplit=-1)\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\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\nstr.swapcase()\n\n   Return a copy of the string with uppercase characters converted to\n   lowercase and vice versa. Note that it is not necessarily true that\n   ``s.swapcase().swapcase() == s``.\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\nstr.translate(map)\n\n   Return a copy of the *s* where all characters have been mapped\n   through the *map* which must be a dictionary of Unicode ordinals\n   (integers) to Unicode ordinals, strings or ``None``.  Unmapped\n   characters are left untouched. Characters mapped to ``None`` are\n   deleted.\n\n   You can use ``str.maketrans()`` to create a translation map from\n   character-to-character mappings in different formats.\n\n   Note: An even more flexible approach is to create a custom character\n     mapping codec using the ``codecs`` module (see\n     ``encodings.cp1251`` 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   The uppercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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',
  'strings': '\nString and Bytes literals\n*************************\n\nString literals are described by the following lexical definitions:\n\n   stringliteral   ::= [stringprefix](shortstring | longstring)\n   stringprefix    ::= "r" | "u" | "R" | "U"\n   shortstring     ::= "\'" shortstringitem* "\'" | \'"\' shortstringitem* \'"\'\n   longstring      ::= "\'\'\'" longstringitem* "\'\'\'" | \'"""\' longstringitem* \'"""\'\n   shortstringitem ::= shortstringchar | stringescapeseq\n   longstringitem  ::= longstringchar | stringescapeseq\n   shortstringchar ::= <any source character except "\\" or newline or the quote>\n   longstringchar  ::= <any source character except "\\">\n   stringescapeseq ::= "\\" <any source character>\n\n   bytesliteral   ::= bytesprefix(shortbytes | longbytes)\n   bytesprefix    ::= "b" | "B" | "br" | "Br" | "bR" | "BR" | "rb" | "rB" | "Rb" | "RB"\n   shortbytes     ::= "\'" shortbytesitem* "\'" | \'"\' shortbytesitem* \'"\'\n   longbytes      ::= "\'\'\'" longbytesitem* "\'\'\'" | \'"""\' longbytesitem* \'"""\'\n   shortbytesitem ::= shortbyteschar | bytesescapeseq\n   longbytesitem  ::= longbyteschar | bytesescapeseq\n   shortbyteschar ::= <any ASCII character except "\\" or newline or the quote>\n   longbyteschar  ::= <any ASCII character except "\\">\n   bytesescapeseq ::= "\\" <any ASCII character>\n\nOne syntactic restriction not indicated by these productions is that\nwhitespace is not allowed between the ``stringprefix`` or\n``bytesprefix`` and the rest of the literal. The source character set\nis defined by the encoding declaration; it is UTF-8 if no encoding\ndeclaration is given in the source file; see section *Encoding\ndeclarations*.\n\nIn plain English: Both types of literals can be enclosed in matching\nsingle quotes (``\'``) or double quotes (``"``).  They can also be\nenclosed in matching groups of three single or double quotes (these\nare generally referred to as *triple-quoted strings*).  The backslash\n(``\\``) character is used to escape characters that otherwise have a\nspecial meaning, such as newline, backslash itself, or the quote\ncharacter.\n\nBytes literals are always prefixed with ``\'b\'`` or ``\'B\'``; they\nproduce an instance of the ``bytes`` type instead of the ``str`` type.\nThey may only contain ASCII characters; bytes with a numeric value of\n128 or greater must be expressed with escapes.\n\nAs of Python 3.3 it is possible again to prefix unicode strings with a\n``u`` prefix to simplify maintenance of dual 2.x and 3.x codebases.\n\nBoth string and bytes literals may optionally be prefixed with a\nletter ``\'r\'`` or ``\'R\'``; such strings are called *raw strings* and\ntreat backslashes as literal characters.  As a result, in string\nliterals, ``\'\\U\'`` and ``\'\\u\'`` escapes in raw strings are not treated\nspecially. Given that Python 2.x\'s raw unicode literals behave\ndifferently than Python 3.x\'s the ``\'ur\'`` syntax is not supported.\n\n   New in version 3.3: The ``\'rb\'`` prefix of raw bytes literals has\n   been added as a synonym of ``\'br\'``.\n\n   New in version 3.3: Support for the unicode legacy literal\n   (``u\'value\'``) was reintroduced to simplify the maintenance of dual\n   Python 2.x and 3.x codebases. See **PEP 414** for more information.\n\nIn triple-quoted strings, unescaped newlines and quotes are allowed\n(and are retained), except that three unescaped quotes in a row\nterminate the string.  (A "quote" is the character used to open the\nstring, i.e. either ``\'`` or ``"``.)\n\nUnless an ``\'r\'`` or ``\'R\'`` prefix is present, escape sequences in\nstrings are interpreted according to rules similar to those used by\nStandard C.  The recognized escape sequences are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence   | Meaning                           | Notes   |\n+===================+===================================+=========+\n| ``\\newline``      | Backslash and newline ignored     |         |\n+-------------------+-----------------------------------+---------+\n| ``\\\\``            | Backslash (``\\``)                 |         |\n+-------------------+-----------------------------------+---------+\n| ``\\\'``            | Single quote (``\'``)              |         |\n+-------------------+-----------------------------------+---------+\n| ``\\"``            | Double quote (``"``)              |         |\n+-------------------+-----------------------------------+---------+\n| ``\\a``            | ASCII Bell (BEL)                  |         |\n+-------------------+-----------------------------------+---------+\n| ``\\b``            | ASCII Backspace (BS)              |         |\n+-------------------+-----------------------------------+---------+\n| ``\\f``            | ASCII Formfeed (FF)               |         |\n+-------------------+-----------------------------------+---------+\n| ``\\n``            | ASCII Linefeed (LF)               |         |\n+-------------------+-----------------------------------+---------+\n| ``\\r``            | ASCII Carriage Return (CR)        |         |\n+-------------------+-----------------------------------+---------+\n| ``\\t``            | ASCII Horizontal Tab (TAB)        |         |\n+-------------------+-----------------------------------+---------+\n| ``\\v``            | ASCII Vertical Tab (VT)           |         |\n+-------------------+-----------------------------------+---------+\n| ``\\ooo``          | Character with octal value *ooo*  | (1,3)   |\n+-------------------+-----------------------------------+---------+\n| ``\\xhh``          | Character with hex value *hh*     | (2,3)   |\n+-------------------+-----------------------------------+---------+\n\nEscape sequences only recognized in string literals are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence   | Meaning                           | Notes   |\n+===================+===================================+=========+\n| ``\\N{name}``      | Character named *name* in the     | (4)     |\n|                   | Unicode database                  |         |\n+-------------------+-----------------------------------+---------+\n| ``\\uxxxx``        | Character with 16-bit hex value   | (5)     |\n|                   | *xxxx*                            |         |\n+-------------------+-----------------------------------+---------+\n| ``\\Uxxxxxxxx``    | Character with 32-bit hex value   | (6)     |\n|                   | *xxxxxxxx*                        |         |\n+-------------------+-----------------------------------+---------+\n\nNotes:\n\n1. As in Standard C, up to three octal digits are accepted.\n\n2. Unlike in Standard C, exactly two hex digits are required.\n\n3. In a bytes literal, hexadecimal and octal escapes denote the byte\n   with the given value. In a string literal, these escapes denote a\n   Unicode character with the given value.\n\n4. Changed in version 3.3: Support for name aliases [1] has been\n   added.\n\n5. Individual code units which form parts of a surrogate pair can be\n   encoded using this escape sequence.  Exactly four hex digits are\n   required.\n\n6. Any Unicode character can be encoded this way, but characters\n   outside the Basic Multilingual Plane (BMP) will be encoded using a\n   surrogate pair if Python is compiled to use 16-bit code units (the\n   default).  Exactly eight hex digits are required.\n\nUnlike Standard C, all unrecognized escape sequences are left in the\nstring unchanged, i.e., *the backslash is left in the string*.  (This\nbehavior is useful when debugging: if an escape sequence is mistyped,\nthe resulting output is more easily recognized as broken.)  It is also\nimportant to note that the escape sequences only recognized in string\nliterals fall into the category of unrecognized escapes for bytes\nliterals.\n\nEven in a raw string, string quotes can be escaped with a backslash,\nbut the backslash remains in the string; for example, ``r"\\""`` is a\nvalid string literal consisting of two characters: a backslash and a\ndouble quote; ``r"\\"`` is not a valid string literal (even a raw\nstring cannot end in an odd number of backslashes).  Specifically, *a\nraw string cannot end in a single backslash* (since the backslash\nwould escape the following quote character).  Note also that a single\nbackslash followed by a newline is interpreted as those two characters\nas part of the string, *not* as a line continuation.\n',
  'subscriptions': '\nSubscriptions\n*************\n\nA subscription selects an item of a sequence (string, tuple or list)\nor mapping (dictionary) object:\n\n   subscription ::= primary "[" expression_list "]"\n\nThe primary must evaluate to an object that supports subscription,\ne.g. a list or dictionary.  User-defined objects can support\nsubscription by defining a ``__getitem__()`` method.\n\nFor built-in objects, there are two types of objects that support\nsubscription:\n\nIf the primary is a mapping, the expression list must evaluate to an\nobject whose value is one of the keys of the mapping, and the\nsubscription selects the value in the mapping that corresponds to that\nkey.  (The expression list is a tuple except if it has exactly one\nitem.)\n\nIf the primary is a sequence, the expression (list) must evaluate to\nan integer or a slice (as discussed in the following section).\n\nThe formal syntax makes no special provision for negative indices in\nsequences; however, built-in sequences all provide a ``__getitem__()``\nmethod that interprets negative indices by adding the length of the\nsequence to the index (so that ``x[-1]`` selects the last item of\n``x``).  The resulting value must be a nonnegative integer less than\nthe number of items in the sequence, and the subscription selects the\nitem whose index is that value (counting from zero). Since the support\nfor negative indices and slicing occurs in the object\'s\n``__getitem__()`` method, subclasses overriding this method will need\nto explicitly add that support.\n\nA string\'s items are characters.  A character is not a separate data\ntype but a string of exactly one character.\n',
  'truth': "\nTruth Value Testing\n*******************\n\nAny object can be tested for truth value, for use in an ``if`` or\n``while`` condition or as operand of the Boolean operations below. The\nfollowing values are considered false:\n\n* ``None``\n\n* ``False``\n\n* zero of any numeric type, for example, ``0``, ``0.0``, ``0j``.\n\n* any empty sequence, for example, ``''``, ``()``, ``[]``.\n\n* any empty mapping, for example, ``{}``.\n\n* instances of user-defined classes, if the class defines a\n  ``__bool__()`` or ``__len__()`` method, when that method returns the\n  integer zero or ``bool`` value ``False``. [1]\n\nAll other values are considered true --- so objects of many types are\nalways true.\n\nOperations and built-in functions that have a Boolean result always\nreturn ``0`` or ``False`` for false and ``1`` or ``True`` for true,\nunless otherwise stated. (Important exception: the Boolean operations\n``or`` and ``and`` always return one of their operands.)\n",
  'try': '\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n   try_stmt  ::= try1_stmt | try2_stmt\n   try1_stmt ::= "try" ":" suite\n                 ("except" [expression ["as" target]] ":" suite)+\n                 ["else" ":" suite]\n                 ["finally" ":" suite]\n   try2_stmt ::= "try" ":" suite\n                 "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started.  This search inspects the except\nclauses in turn until one is found that matches the exception.  An\nexpression-less except clause, if present, must be last; it matches\nany exception.  For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception.  An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed.  All except\nclauses must have an executable block.  When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause.  This is as if\n\n   except E as N:\n       foo\n\nwas translated to\n\n   except E as N:\n       try:\n           foo\n       finally:\n           del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause.  Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting of\nthe exception class, the exception instance and a traceback object\n(see section *The standard type hierarchy*) identifying the point in\nthe program where the exception occurred.  ``sys.exc_info()`` values\nare restored to their previous values (before the call) when returning\nfrom a function that 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 set as the context of the new exception.  The exception\ninformation is not available to the program during execution of the\n``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n',
- 'types': '\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.), although such additions\nwill often be provided via the standard library instead.\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 literal ``...`` or the\n   built-in name ``Ellipsis``.  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 two types of integers:\n\n      Integers (``int``)\n\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 (``bool``)\n         These represent the truth values False and True.  The two\n         objects representing the values False and True are the only\n         Boolean objects. The Boolean type is a subtype of the integer\n         type, and Boolean values behave like the values 0 and 1,\n         respectively, in almost all contexts, the exception being\n         that when converted to a string, the strings ``"False"`` or\n         ``"True"`` are returned, respectively.\n\n      The rules for integer representation are intended to give the\n      most meaningful interpretation of shift and mask operations\n      involving negative integers.\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`` (``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         A string is a sequence of values that represent Unicode\n         codepoints. All the codepoints in range ``U+0000 - U+10FFFF``\n         can be represented in a string.  Python doesn\'t have a\n         ``chr`` type, and every character in the string is\n         represented as a string object with length ``1``.  The built-\n         in function ``ord()`` converts a character to its codepoint\n         (as an integer); ``chr()`` converts an integer in range ``0 -\n         10FFFF`` to the corresponding character. ``str.encode()`` can\n         be used to convert a ``str`` to ``bytes`` using the given\n         encoding, and ``bytes.decode()`` can be used to achieve the\n         opposite.\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      Bytes\n         A bytes object is an immutable array.  The items are 8-bit\n         bytes, represented by integers in the range 0 <= x < 256.\n         Bytes literals (like ``b\'abc\'`` and the built-in function\n         ``bytes()`` can be used to construct bytes objects.  Also,\n         bytes objects can be decoded to strings via the ``decode()``\n         method.\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, as does the ``collections`` module.\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.ndbm`` and ``dbm.gnu`` provide\n      additional examples of mapping types, as does the\n      ``collections`` module.\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      |                           | string, or ``None`` if          |             |\n      |                           | unavailable                     |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__name__``              | The function\'s name             | Writable    |\n      +---------------------------+---------------------------------+-------------+\n      | ``__qualname__``          | The function\'s *qualified name* | Writable    |\n      |                           | New in version 3.3.             |             |\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      |                           | 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      |                           | the compiled function body.     |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__globals__``           | A reference to the dictionary   | Read-only   |\n      |                           | that holds the function\'s       |             |\n      |                           | global variables --- the global |             |\n      |                           | namespace of the module in      |             |\n      |                           | which the function was defined. |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__dict__``              | The namespace supporting        | Writable    |\n      |                           | arbitrary function attributes.  |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__closure__``           | ``None`` or a tuple of cells    | Read-only   |\n      |                           | that contain bindings for the   |             |\n      |                           | function\'s free variables.      |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__annotations__``       | A dict containing annotations   | Writable    |\n      |                           | of parameters.  The keys of the |             |\n      |                           | dict are the parameter names,   |             |\n      |                           | or ``\'return\'`` for the return  |             |\n      |                           | annotation, if provided.        |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__kwdefaults__``        | A dict containing defaults for  | Writable    |\n      |                           | keyword-only parameters.        |             |\n      +---------------------------+---------------------------------+-------------+\n\n      Most of the attributes labelled "Writable" check the type of the\n      assigned value.\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   Instance methods\n      An instance method object combines a class, a class instance and\n      any callable object (normally a user-defined function).\n\n      Special read-only attributes: ``__self__`` is the class instance\n      object, ``__func__`` is the function object; ``__doc__`` is the\n      method\'s documentation (same as ``__func__.__doc__``);\n      ``__name__`` is the method name (same as ``__func__.__name__``);\n      ``__module__`` is the name of the module the method was defined\n      in, or ``None`` if unavailable.\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 or a class\n      method object.\n\n      When an instance method object is created by retrieving a user-\n      defined function object from a class via one of its instances,\n      its ``__self__`` attribute is the instance, and the method\n      object is said to be bound.  The new method\'s ``__func__``\n      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 ``__func__``\n      attribute of the new instance is not the original method object\n      but its ``__func__`` attribute.\n\n      When an instance method object is created by retrieving a class\n      method object from a class or instance, its ``__self__``\n      attribute is the class itself, and its ``__func__`` attribute is\n      the function object underlying the class method.\n\n      When an instance method object is called, the underlying\n      function (``__func__``) is called, inserting the class instance\n      (``__self__``) in front of the argument list.  For instance,\n      when ``C`` is a class which contains a definition for a function\n      ``f()``, and ``x`` is an instance of ``C``, calling ``x.f(1)``\n      is equivalent to calling ``C.f(x, 1)``.\n\n      When an instance method object is derived from a class method\n      object, the "class instance" stored in ``__self__`` will\n      actually be the class itself, so that calling either ``x.f(1)``\n      or ``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 instance\n      method object happens each time the attribute is retrieved from\n      the instance.  In some cases, a fruitful optimization is to\n      assign the attribute to a local variable and call that local\n      variable. Also notice that this transformation only happens for\n      user-defined functions; other callable objects (and all non-\n      callable objects) are retrieved without transformation.  It is\n      also important to note that user-defined functions which are\n      attributes of a class instance are not converted to bound\n      methods; this *only* happens when the function is an attribute\n      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   Classes\n      Classes are callable.  These objects normally act as factories\n      for new instances of themselves, but variations are possible for\n      class types that override ``__new__()``.  The arguments of the\n      call are passed to ``__new__()`` and, in the typical case, to\n      ``__init__()`` to initialize the new instance.\n\n   Class Instances\n      Instances of arbitrary classes can be made callable by defining\n      a ``__call__()`` method in their class.\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   __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\nCustom classes\n   Custom class types are typically created by class definitions (see\n   section *Class definitions*).  A class has a namespace implemented\n   by a dictionary object. Class attribute references are translated\n   to lookups in this dictionary, e.g., ``C.x`` is translated to\n   ``C.__dict__["x"]`` (although there are a number of hooks which\n   allow for other means of locating attributes). When the attribute\n   name is not found there, the attribute search continues in the base\n   classes. This search of the base classes uses the C3 method\n   resolution order which behaves correctly even in the presence of\n   \'diamond\' inheritance structures where there are multiple\n   inheritance paths leading back to a common ancestor. Additional\n   details on the C3 MRO used by Python can be found in the\n   documentation accompanying the 2.3 release at\n   http://www.python.org/download/releases/2.3/mro/.\n\n   When a class attribute reference (for class ``C``, say) would yield\n   a class method object, it is transformed into an instance method\n   object whose ``__self__`` attributes is ``C``.  When it would yield\n   a static method object, it is transformed into the object wrapped\n   by the static method object. See section *Implementing Descriptors*\n   for another way in which attributes retrieved from a class may\n   differ from those actually contained in its ``__dict__``.\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, it is transformed into an instance method object\n   whose ``__self__`` attribute is the instance.  Static method and\n   class method objects are also transformed; see above under\n   "Classes".  See section *Implementing Descriptors* for another way\n   in which attributes of a class retrieved via its instances may\n   differ from the objects actually stored in the class\'s\n   ``__dict__``.  If no class attribute is found, and the object\'s\n   class has a ``__getattr__()`` method, that is called to satisfy the\n   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\nI/O objects (also known as file objects)\n   A *file object* represents an open file.  Various shortcuts are\n   available to create file objects: the ``open()`` built-in function,\n   and also ``os.popen()``, ``os.fdopen()``, and the ``makefile()``\n   method of socket objects (and perhaps by other functions or methods\n   provided by extension modules).\n\n   The objects ``sys.stdin``, ``sys.stdout`` and ``sys.stderr`` are\n   initialized to file objects corresponding to the interpreter\'s\n   standard input, output and error streams; they are all open in text\n   mode and therefore follow the interface defined by the\n   ``io.TextIOBase`` abstract class.\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_lasti`` gives the precise instruction (this is an index into\n      the bytecode string 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_lineno`` is the current line number\n      of the frame --- writing to this from within a trace function\n      jumps to the given line (only for the bottom-most frame).  A\n      debugger can implement a Jump command (aka Set Next Statement)\n      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 the third item of the\n      tuple returned by ``sys.exc_info()``. When the program contains\n      no suitable handler, the stack trace is written (nicely\n      formatted) to the standard error stream; if the interpreter is\n      interactive, it is also made available to the user as\n      ``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 for ``__getitem__()``\n      methods.  They are also created by the built-in ``slice()``\n      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 slice that the slice object\n         would describe if applied to a sequence of *length* items.\n         It returns a tuple of three integers; respectively these are\n         the *start* and *stop* indices and the *step* or stride\n         length of the slice. Missing or out-of-bounds indices are\n         handled in a manner consistent with regular slices.\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',
+ '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.), although such additions\nwill often be provided via the standard library instead.\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 literal ``...`` or the\n   built-in name ``Ellipsis``.  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 two types of integers:\n\n      Integers (``int``)\n\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 (``bool``)\n         These represent the truth values False and True.  The two\n         objects representing the values False and True are the only\n         Boolean objects. The Boolean type is a subtype of the integer\n         type, and Boolean values behave like the values 0 and 1,\n         respectively, in almost all contexts, the exception being\n         that when converted to a string, the strings ``"False"`` or\n         ``"True"`` are returned, respectively.\n\n      The rules for integer representation are intended to give the\n      most meaningful interpretation of shift and mask operations\n      involving negative integers.\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`` (``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         A string is a sequence of values that represent Unicode\n         codepoints. All the codepoints in range ``U+0000 - U+10FFFF``\n         can be represented in a string.  Python doesn\'t have a\n         ``chr`` type, and every character in the string is\n         represented as a string object with length ``1``.  The built-\n         in function ``ord()`` converts a character to its codepoint\n         (as an integer); ``chr()`` converts an integer in range ``0 -\n         10FFFF`` to the corresponding character. ``str.encode()`` can\n         be used to convert a ``str`` to ``bytes`` using the given\n         encoding, and ``bytes.decode()`` can be used to achieve the\n         opposite.\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      Bytes\n         A bytes object is an immutable array.  The items are 8-bit\n         bytes, represented by integers in the range 0 <= x < 256.\n         Bytes literals (like ``b\'abc\'`` and the built-in function\n         ``bytes()`` can be used to construct bytes objects.  Also,\n         bytes objects can be decoded to strings via the ``decode()``\n         method.\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, as does the ``collections`` module.\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.ndbm`` and ``dbm.gnu`` provide\n      additional examples of mapping types, as does the\n      ``collections`` module.\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      |                           | string, or ``None`` if          |             |\n      |                           | unavailable                     |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__name__``              | The function\'s name             | Writable    |\n      +---------------------------+---------------------------------+-------------+\n      | ``__qualname__``          | The function\'s *qualified name* | Writable    |\n      |                           | New in version 3.3.             |             |\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      |                           | 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      |                           | the compiled function body.     |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__globals__``           | A reference to the dictionary   | Read-only   |\n      |                           | that holds the function\'s       |             |\n      |                           | global variables --- the global |             |\n      |                           | namespace of the module in      |             |\n      |                           | which the function was defined. |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__dict__``              | The namespace supporting        | Writable    |\n      |                           | arbitrary function attributes.  |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__closure__``           | ``None`` or a tuple of cells    | Read-only   |\n      |                           | that contain bindings for the   |             |\n      |                           | function\'s free variables.      |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__annotations__``       | A dict containing annotations   | Writable    |\n      |                           | of parameters.  The keys of the |             |\n      |                           | dict are the parameter names,   |             |\n      |                           | or ``\'return\'`` for the return  |             |\n      |                           | annotation, if provided.        |             |\n      +---------------------------+---------------------------------+-------------+\n      | ``__kwdefaults__``        | A dict containing defaults for  | Writable    |\n      |                           | keyword-only parameters.        |             |\n      +---------------------------+---------------------------------+-------------+\n\n      Most of the attributes labelled "Writable" check the type of the\n      assigned value.\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   Instance methods\n      An instance method object combines a class, a class instance and\n      any callable object (normally a user-defined function).\n\n      Special read-only attributes: ``__self__`` is the class instance\n      object, ``__func__`` is the function object; ``__doc__`` is the\n      method\'s documentation (same as ``__func__.__doc__``);\n      ``__name__`` is the method name (same as ``__func__.__name__``);\n      ``__module__`` is the name of the module the method was defined\n      in, or ``None`` if unavailable.\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 or a class\n      method object.\n\n      When an instance method object is created by retrieving a user-\n      defined function object from a class via one of its instances,\n      its ``__self__`` attribute is the instance, and the method\n      object is said to be bound.  The new method\'s ``__func__``\n      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 ``__func__``\n      attribute of the new instance is not the original method object\n      but its ``__func__`` attribute.\n\n      When an instance method object is created by retrieving a class\n      method object from a class or instance, its ``__self__``\n      attribute is the class itself, and its ``__func__`` attribute is\n      the function object underlying the class method.\n\n      When an instance method object is called, the underlying\n      function (``__func__``) is called, inserting the class instance\n      (``__self__``) in front of the argument list.  For instance,\n      when ``C`` is a class which contains a definition for a function\n      ``f()``, and ``x`` is an instance of ``C``, calling ``x.f(1)``\n      is equivalent to calling ``C.f(x, 1)``.\n\n      When an instance method object is derived from a class method\n      object, the "class instance" stored in ``__self__`` will\n      actually be the class itself, so that calling either ``x.f(1)``\n      or ``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 instance\n      method object happens each time the attribute is retrieved from\n      the instance.  In some cases, a fruitful optimization is to\n      assign the attribute to a local variable and call that local\n      variable. Also notice that this transformation only happens for\n      user-defined functions; other callable objects (and all non-\n      callable objects) are retrieved without transformation.  It is\n      also important to note that user-defined functions which are\n      attributes of a class instance are not converted to bound\n      methods; this *only* happens when the function is an attribute\n      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   Classes\n      Classes are callable.  These objects normally act as factories\n      for new instances of themselves, but variations are possible for\n      class types that override ``__new__()``.  The arguments of the\n      call are passed to ``__new__()`` and, in the typical case, to\n      ``__init__()`` to initialize the new instance.\n\n   Class Instances\n      Instances of arbitrary classes can be made callable by defining\n      a ``__call__()`` method in their class.\n\nModules\n   Modules are a basic organizational unit of Python code, and are\n   created by the *import system* as invoked either by the ``import``\n   statement (see ``import``), or by calling functions such as\n   ``importlib.import_module()`` and built-in ``__import__()``.  A\n   module object has a namespace implemented by a dictionary object\n   (this is the dictionary referenced by the ``__globals__`` attribute\n   of functions defined in the module).  Attribute references are\n   translated to lookups in this dictionary, e.g., ``m.x`` is\n   equivalent to ``m.__dict__["x"]``. A module object does not contain\n   the code object used to initialize the module (since it isn\'t\n   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 may be missing for certain types of modules,\n   such as C modules that are statically linked into the interpreter;\n   for extension modules loaded dynamically from a shared library, it\n   is the pathname of the shared library file.\n\nCustom classes\n   Custom class types are typically created by class definitions (see\n   section *Class definitions*).  A class has a namespace implemented\n   by a dictionary object. Class attribute references are translated\n   to lookups in this dictionary, e.g., ``C.x`` is translated to\n   ``C.__dict__["x"]`` (although there are a number of hooks which\n   allow for other means of locating attributes). When the attribute\n   name is not found there, the attribute search continues in the base\n   classes. This search of the base classes uses the C3 method\n   resolution order which behaves correctly even in the presence of\n   \'diamond\' inheritance structures where there are multiple\n   inheritance paths leading back to a common ancestor. Additional\n   details on the C3 MRO used by Python can be found in the\n   documentation accompanying the 2.3 release at\n   http://www.python.org/download/releases/2.3/mro/.\n\n   When a class attribute reference (for class ``C``, say) would yield\n   a class method object, it is transformed into an instance method\n   object whose ``__self__`` attributes is ``C``.  When it would yield\n   a static method object, it is transformed into the object wrapped\n   by the static method object. See section *Implementing Descriptors*\n   for another way in which attributes retrieved from a class may\n   differ from those actually contained in its ``__dict__``.\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, it is transformed into an instance method object\n   whose ``__self__`` attribute is the instance.  Static method and\n   class method objects are also transformed; see above under\n   "Classes".  See section *Implementing Descriptors* for another way\n   in which attributes of a class retrieved via its instances may\n   differ from the objects actually stored in the class\'s\n   ``__dict__``.  If no class attribute is found, and the object\'s\n   class has a ``__getattr__()`` method, that is called to satisfy the\n   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\nI/O objects (also known as file objects)\n   A *file object* represents an open file.  Various shortcuts are\n   available to create file objects: the ``open()`` built-in function,\n   and also ``os.popen()``, ``os.fdopen()``, and the ``makefile()``\n   method of socket objects (and perhaps by other functions or methods\n   provided by extension modules).\n\n   The objects ``sys.stdin``, ``sys.stdout`` and ``sys.stderr`` are\n   initialized to file objects corresponding to the interpreter\'s\n   standard input, output and error streams; they are all open in text\n   mode and therefore follow the interface defined by the\n   ``io.TextIOBase`` abstract class.\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_lasti`` gives the precise instruction (this is an index into\n      the bytecode string 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_lineno`` is the current line number\n      of the frame --- writing to this from within a trace function\n      jumps to the given line (only for the bottom-most frame).  A\n      debugger can implement a Jump command (aka Set Next Statement)\n      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 the third item of the\n      tuple returned by ``sys.exc_info()``. When the program contains\n      no suitable handler, the stack trace is written (nicely\n      formatted) to the standard error stream; if the interpreter is\n      interactive, it is also made available to the user as\n      ``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 for ``__getitem__()``\n      methods.  They are also created by the built-in ``slice()``\n      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 slice that the slice object\n         would describe if applied to a sequence of *length* items.\n         It returns a tuple of three integers; respectively these are\n         the *start* and *stop* indices and the *step* or stride\n         length of the slice. Missing or out-of-bounds indices are\n         handled in a manner consistent with regular slices.\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([arg])\n\n   Return a new dictionary initialized from an optional positional\n   argument or from a set of keyword arguments.  If no arguments are\n   given, return a new empty dictionary.  If the positional argument\n   *arg* is a mapping object, return a dictionary mapping the same\n   keys to the same values as does the mapping object.  Otherwise the\n   positional argument must be a sequence, a container that supports\n   iteration, or an iterator object.  The elements of the argument\n   must each also be of one of those kinds, and each must in turn\n   contain exactly two objects.  The first is used as a key in the new\n   dictionary, and the second as the key\'s value.  If a given key is\n   seen more than once, the last value associated with it is retained\n   in the new dictionary.\n\n   If keyword arguments are given, the keywords themselves with their\n   associated values are added as items to the dictionary.  If a key\n   is specified both in the positional argument and as a keyword\n   argument, the value associated with the keyword is retained in the\n   dictionary.  For example, these all return a dictionary equal to\n   ``{"one": 1, "two": 2}``:\n\n   * ``dict(one=1, two=2)``\n\n   * ``dict({\'one\': 1, \'two\': 2})``\n\n   * ``dict(zip((\'one\', \'two\'), (1, 2)))``\n\n   * ``dict([[\'two\', 2], [\'one\', 1]])``\n\n   The first example only works for keys that are valid Python\n   identifiers; the others work with any valid keys.\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      If a subclass of dict defines a method ``__missing__()``, if the\n      key *key* is not present, the ``d[key]`` operation calls that\n      method with the key *key* as argument.  The ``d[key]`` operation\n      then returns or raises whatever is returned or raised by the\n      ``__missing__(key)`` call if the key is not present. No other\n      operations or methods invoke ``__missing__()``. If\n      ``__missing__()`` is not defined, ``KeyError`` is raised.\n      ``__missing__()`` must be a method; it cannot be an instance\n      variable:\n\n         >>> class Counter(dict):\n         ...     def __missing__(self, key):\n         ...         return 0\n         >>> c = Counter()\n         >>> c[\'red\']\n         0\n         >>> c[\'red\'] += 1\n         >>> c[\'red\']\n         1\n\n      See ``collections.Counter`` for a complete implementation\n      including other methods helpful for accumulating and managing\n      tallies.\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   key not in d\n\n      Equivalent to ``not key in d``.\n\n   iter(d)\n\n      Return an iterator over the keys of the dictionary.  This is a\n      shortcut for ``iter(d.keys())``.\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   classmethod 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   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   items()\n\n      Return a new view of the dictionary\'s items (``(key, value)``\n      pairs). See the *documentation of view objects*.\n\n   keys()\n\n      Return a new view of the dictionary\'s keys.  See the\n      *documentation of view objects*.\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   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   values()\n\n      Return a new view of the dictionary\'s values.  See the\n      *documentation of view objects*.\n\nSee also:\n\n   ``types.MappingProxyType`` can be used to create a read-only view\n   of a ``dict``.\n\n\nDictionary view objects\n=======================\n\nThe objects returned by ``dict.keys()``, ``dict.values()`` and\n``dict.items()`` are *view objects*.  They provide a dynamic view on\nthe 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\nand hashable, then the items view is also set-like.  (Values views are\nnot treated as set-like since the entries are generally not unique.)\nFor set-like views, all of the operations defined for the abstract\nbase class ``collections.Set`` are available (for example, ``==``,\n``<``, or ``^``).\n\nAn example of dictionary view usage:\n\n   >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n   >>> keys = dishes.keys()\n   >>> values = dishes.values()\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   >>> keys ^ {\'sausage\', \'juice\'}\n   {\'juice\', \'sausage\', \'bacon\', \'spam\'}\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\nIf you access a method (a function defined in a class namespace)\nthrough an instance, you get a special object: a *bound method* (also\ncalled *instance method*) object. When called, it will add the\n``self`` argument to the argument list.  Bound methods have two\nspecial read-only attributes: ``m.__self__`` is the object on which\nthe method operates, and ``m.__func__`` is the function implementing\nthe method.  Calling ``m(arg-1, arg-2, ..., arg-n)`` is completely\nequivalent to calling ``m.__func__(m.__self__, arg-1, arg-2, ...,\narg-n)``.\n\nLike function objects, bound method objects support getting arbitrary\nattributes.  However, since method attributes are actually stored on\nthe underlying function object (``meth.__func__``), setting method\nattributes on bound methods is disallowed.  Attempting to set a method\nattribute results in a ``TypeError`` being raised.  In order to set a\nmethod attribute, you need to explicitly set it on the underlying\nfunction object:\n\n   class C:\n       def method(self):\n           pass\n\n   c = C()\n   c.method.__func__.whoami = 'my name is c'\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``, ``bytes``, ``bytearray``, ``list``, ``tuple``, ``range``\n************************************************************************************\n\nThere are six sequence types: strings, byte sequences (``bytes``\nobjects), byte arrays (``bytearray`` objects), lists, tuples, and\nrange objects.  For other containers see the built in ``dict`` and\n``set`` classes, and the ``collections`` module.\n\nStrings contain Unicode characters.  Their literals are written in\nsingle or double quotes: ``\'xyzzy\'``, ``"frobozz"``.  See *String and\nBytes literals* for more about string literals.  In addition to the\nfunctionality described here, there are also string-specific methods\ndescribed in the *String Methods* section.\n\nBytes and bytearray objects contain single bytes -- the former is\nimmutable while the latter is a mutable sequence. Bytes objects can be\nconstructed by using the constructor, ``bytes()``, and from literals;\nuse a ``b`` prefix with normal string syntax: ``b\'xyzzy\'``.  To\nconstruct byte arrays, use the ``bytearray()`` function.\n\nWhile string objects are sequences of characters (represented by\nstrings of length 1), bytes and bytearray objects are sequences of\n*integers* (between 0 and 255), representing the ASCII value of single\nbytes.  That means that for a bytes or bytearray object *b*, ``b[0]``\nwill be an integer, while ``b[0:1]`` will be a bytes or bytearray\nobject of length 1.  The representation of bytes objects uses the\nliteral format (``b\'...\'``) since it is generally more useful than\ne.g. ``bytes([50, 19, 100])``.  You can always convert a bytes object\ninto a list of integers using ``list(b)``.\n\nAlso, while in previous Python versions, byte strings and Unicode\nstrings could be exchanged for each other rather freely (barring\nencoding issues), strings and bytes are now completely separate\nconcepts.  There\'s no implicit en-/decoding if you pass an object of\nthe wrong type.  A string always compares unequal to a bytes or\nbytearray object.\n\nLists are constructed with square brackets, separating items with\ncommas: ``[a, b, c]``.  Tuples are constructed by the comma operator\n(not within square brackets), with or without enclosing parentheses,\nbut an empty tuple must have the enclosing parentheses, such as ``a,\nb, c`` or ``()``.  A single item tuple must have a trailing comma,\nsuch as ``(d,)``.\n\nObjects of type range are created using the ``range()`` function.\nThey don\'t support concatenation or repetition, and using ``min()`` or\n``max()`` on them 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*, *j* and *k* 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(i)``     | index of the first occurence of  |            |\n|                    | *i* in *s*                       |            |\n+--------------------+----------------------------------+------------+\n| ``s.count(i)``     | total number of occurences of    |            |\n|                    | *i* 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\ncompare equal and the two sequences must be of the same type and have\nthe same length.  (For full details see *Comparisons* in the language\nreference.)\n\nNotes:\n\n1. When *s* is a string object, the ``in`` and ``not in`` operations\n   act like a substring test.\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. Concatenating immutable strings always results in a new object.\n   This means that building up a string by repeated concatenation will\n   have a quadratic runtime cost in the total string length.  To get a\n   linear runtime cost, you must switch to one of the alternatives\n   below:\n\n   * if concatenating ``str`` objects, you can build a list and use\n     ``str.join()`` at the end;\n\n   * if concatenating ``bytes`` objects, you can similarly use\n     ``bytes.join()``, or you can do in-place concatenation with a\n     ``bytearray`` object.  ``bytearray`` objects are mutable and have\n     an efficient overallocation mechanism.\n\n\nString Methods\n==============\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n   Return a copy of the string with its first character capitalized\n   and the rest lowercased.\n\nstr.casefold()\n\n   Return a casefolded copy of the string. Casefolded strings may be\n   used for caseless matching.\n\n   Casefolding is similar to lowercasing but more aggressive because\n   it is intended to remove all case distinctions in a string. For\n   example, the German lowercase letter ``\'\xc3\x9f\'`` is equivalent to\n   ``"ss"``. Since it is already lowercase, ``lower()`` would do\n   nothing to ``\'\xc3\x9f\'``; ``casefold()`` converts it to ``"ss"``.\n\n   The casefolding algorithm is described in section 3.13 of the\n   Unicode Standard.\n\n   New in version 3.3.\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\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.encode(encoding="utf-8", errors="strict")\n\n   Return an encoded version of the string as a bytes object. Default\n   encoding is ``\'utf-8\'``. *errors* may be given to set a different\n   error handling scheme. The default for *errors* is ``\'strict\'``,\n   meaning that encoding errors raise a ``UnicodeError``. Other\n   possible values are ``\'ignore\'``, ``\'replace\'``,\n   ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n   registered via ``codecs.register_error()``, see section *Codec Base\n   Classes*. For a list of possible encodings, see section *Standard\n   Encodings*.\n\n   Changed in version 3.1: 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\nstr.expandtabs([tabsize])\n\n   Return a copy of the string where all tab characters are replaced\n   by zero or more spaces, depending on the current column and the\n   given tab size.  The column number is reset to zero after each\n   newline occurring in the string. If *tabsize* is not given, a tab\n   size of ``8`` characters is assumed.  This doesn\'t understand other\n   non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n   Return the lowest index in the string where substring *sub* is\n   found, such that *sub* is contained in the slice ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` if *sub* is not found.\n\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\nstr.format_map(mapping)\n\n   Similar to ``str.format(**mapping)``, except that ``mapping`` is\n   used directly and not copied to a ``dict`` .  This is useful if for\n   example ``mapping`` is a dict subclass:\n\n   >>> class Default(dict):\n   ...     def __missing__(self, key):\n   ...         return key\n   ...\n   >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n   \'Guido was born in country\'\n\n   New in version 3.2.\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.  A character\n   ``c`` is alphanumeric if one of the following returns ``True``:\n   ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n   ``c.isnumeric()``.\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.  Alphabetic\n   characters are those characters defined in the Unicode character\n   database as "Letter", i.e., those with general category property\n   being one of "Lm", "Lt", "Lu", "Ll", or "Lo".  Note that this is\n   different from the "Alphabetic" property defined in the Unicode\n   Standard.\n\nstr.isdecimal()\n\n   Return true if all characters in the string are decimal characters\n   and there is at least one character, false otherwise. Decimal\n   characters are those from general category "Nd". This category\n   includes digit characters, and all characters that can be used to\n   form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\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.  Digits include decimal\n   characters and digits that need special handling, such as the\n   compatibility superscript digits.  Formally, a digit is a character\n   that has the property value Numeric_Type=Digit or\n   Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n   Return true if the string is a valid identifier according to the\n   language definition, section *Identifiers and keywords*.\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\nstr.isnumeric()\n\n   Return true if all characters in the string are numeric characters,\n   and there is at least one character, false otherwise. Numeric\n   characters include digit characters, and all characters that have\n   the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n   ONE FIFTH.  Formally, numeric characters are those with the\n   property value Numeric_Type=Digit, Numeric_Type=Decimal or\n   Numeric_Type=Numeric.\n\nstr.isprintable()\n\n   Return true if all characters in the string are printable or the\n   string is empty, false otherwise.  Nonprintable characters are\n   those characters defined in the Unicode character database as\n   "Other" or "Separator", excepting the ASCII space (0x20) which is\n   considered printable.  (Note that printable characters in this\n   context are those which should not be escaped when ``repr()`` is\n   invoked on a string.  It has no bearing on the handling of strings\n   written to ``sys.stdout`` or ``sys.stderr``.)\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.  Whitespace\n   characters  are those characters defined in the Unicode character\n   database as "Other" or "Separator" and those with bidirectional\n   property being one of "WS", "B", or "S".\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\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\nstr.join(iterable)\n\n   Return a string which is the concatenation of the strings in the\n   *iterable* *iterable*.  A ``TypeError`` will be raised if there are\n   any non-string values in *iterable*, including ``bytes`` objects.\n   The separator between elements is the 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\nstr.lower()\n\n   Return a copy of the string with all the cased characters [4]\n   converted to lowercase.\n\n   The lowercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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\nstatic str.maketrans(x[, y[, z]])\n\n   This static method returns a translation table usable for\n   ``str.translate()``.\n\n   If there is only one argument, it must be a dictionary mapping\n   Unicode ordinals (integers) or characters (strings of length 1) to\n   Unicode ordinals, strings (of arbitrary lengths) or None.\n   Character keys will then be converted to ordinals.\n\n   If there are two arguments, they must be strings of equal length,\n   and in the resulting dictionary, each character in x will be mapped\n   to the character at the same position in y.  If there is a third\n   argument, it must be a string, whose characters will be mapped to\n   None in the result.\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\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\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\nstr.rsplit(sep=None, maxsplit=-1)\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\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\nstr.split(sep=None, maxsplit=-1)\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.  Line breaks are not included in the resulting list\n   unless *keepends* is given and true. This method uses the universal\n   newlines approach to splitting lines. Unlike ``split()``, if the\n   string ends with line boundary characters the returned list does\n   ``not`` have an empty last element.\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\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\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\nstr.swapcase()\n\n   Return a copy of the string with uppercase characters converted to\n   lowercase and vice versa. Note that it is not necessarily true that\n   ``s.swapcase().swapcase() == s``.\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\nstr.translate(map)\n\n   Return a copy of the *s* where all characters have been mapped\n   through the *map* which must be a dictionary of Unicode ordinals\n   (integers) to Unicode ordinals, strings or ``None``.  Unmapped\n   characters are left untouched. Characters mapped to ``None`` are\n   deleted.\n\n   You can use ``str.maketrans()`` to create a translation map from\n   character-to-character mappings in different formats.\n\n   Note: An even more flexible approach is to create a custom character\n     mapping codec using the ``codecs`` module (see\n     ``encodings.cp1251`` 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   The uppercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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\nOld String Formatting Operations\n================================\n\nNote: The formatting operations described here are modelled on C\'s\n  printf() syntax.  They only support formatting of certain builtin\n  types.  The use of a binary operator means that care may be needed\n  in order to format tuples and dictionaries correctly.  As the new\n  *String Formatting* syntax is more flexible and handles tuples and\n  dictionaries naturally, it is recommended for new code.  However,\n  there are no current plans to deprecate printf-style formatting.\n\nString objects have one unique built-in operation: the ``%`` operator\n(modulo). This is also known as the string *formatting* or\n*interpolation* operator. Given ``format % values`` (where *format* is\na string), ``%`` conversion specifications in *format* are replaced\nwith zero or more elements of *values*. The effect is similar to the\nusing ``sprintf()`` in the C language.\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\n   precision is read from the next element of the tuple in *values*,\n   and the 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()``).  | (5)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'a\'``      | String (converts any Python object using              | (5)     |\n|              | ``ascii()``).                                         |         |\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. If precision is ``N``, the output is truncated to ``N`` characters.\n\n1. 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 3.1: ``%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\nRange Type\n==========\n\nThe ``range`` type is an immutable sequence which is commonly used for\nlooping.  The advantage of the ``range`` type is that an ``range``\nobject will always take the same amount of memory, no matter the size\nof the range it represents.\n\nRange objects have relatively little behavior: they support indexing,\ncontains, iteration, the ``len()`` function, and the following\nmethods:\n\nrange.count(x)\n\n   Return the number of *i*\'s for which ``s[i] == x``.\n\n   New in version 3.2.\n\nrange.index(x)\n\n   Return the smallest *i* such that ``s[i] == x``.  Raises\n   ``ValueError`` when *x* is not in the range.\n\n   New in version 3.2.\n\n\nMutable Sequence Types\n======================\n\nList and bytearray objects support additional operations that allow\nin-place modification of the object.  Other mutable sequence types\n(when added to the language) should also support these operations.\nStrings and tuples are immutable sequence types: such objects cannot\nbe modified once created. The following operations are defined on\nmutable sequence types (where *x* is an arbitrary object).\n\nNote that while lists allow their items to be of any type, bytearray\nobject "items" are all integers in the range 0 <= x < 256.\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)] =     |                       |\n|                                | [x]``                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (2)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.clear()``                  | remove all items from ``s``      |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.copy()``                   | return a shallow copy of ``s``   |                       |\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    | (3)                   |\n|                                | ``s[k] == x`` and ``i <= k < j`` |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (4)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (5)                   |\n|                                | return x``                       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (3)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()``                | reverses the items of *s* in     | (6)                   |\n|                                | place                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([key[, reverse]])``   | sort the items of *s* in place   | (6), (7), (8)         |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. *x* can be any iterable object.\n\n3. 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 sequence length is added, as for slice indices.  If it\n   is still negative, it is truncated to zero, as for slice indices.\n\n4. When a negative index is passed as the first parameter to the\n   ``insert()`` method, the sequence length is added, as for slice\n   indices.  If it is still negative, it is truncated to zero, as for\n   slice indices.\n\n5. The optional argument *i* defaults to ``-1``, so that by default\n   the last item is removed and returned.\n\n6. The ``sort()`` and ``reverse()`` methods modify the sequence in\n   place for economy of space when sorting or reversing a large\n   sequence.  To remind you that they operate by side effect, they\n   don\'t return the sorted or reversed sequence.\n\n7. The ``sort()`` method takes optional arguments for controlling the\n   comparisons.  Each must be specified as a keyword argument.\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``. Use ``functools.cmp_to_key()`` to\n   convert an old-style *cmp* function to a *key* function.\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   The ``sort()`` method is guaranteed to be stable.  A sort is stable\n   if it guarantees not to change the relative order of elements that\n   compare equal --- this is helpful for sorting in multiple passes\n   (for example, sort by department, then by salary grade).\n\n   **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 makes the list appear\n   empty for the duration, and raises ``ValueError`` if it can detect\n   that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\n\n      New in version 3.3: ``clear()`` and ``copy()`` methods.\n\n\nBytes and Byte Array Methods\n============================\n\nBytes and bytearray objects, being "strings of bytes", have all\nmethods found on strings, with the exception of ``encode()``,\n``format()`` and ``isidentifier()``, which do not make sense with\nthese types.  For converting the objects to strings, they have a\n``decode()`` method.\n\nWherever one of these methods needs to interpret the bytes as\ncharacters (e.g. the ``is...()`` methods), the ASCII character set is\nassumed.\n\nNew in version 3.3: The functions ``count()``, ``find()``,\n``index()``, ``rfind()`` and ``rindex()`` have additional semantics\ncompared to the corresponding string functions: They also accept an\ninteger in range 0 to 255 (a byte) as their first argument.\n\nNote: The methods on bytes and bytearray objects don\'t accept strings as\n  their arguments, just as the methods on strings don\'t accept bytes\n  as their arguments.  For example, you have to write\n\n     a = "abc"\n     b = a.replace("a", "f")\n\n  and\n\n     a = b"abc"\n     b = a.replace(b"a", b"f")\n\nbytes.decode(encoding="utf-8", errors="strict")\nbytearray.decode(encoding="utf-8", errors="strict")\n\n   Return a string decoded from the given bytes.  Default encoding is\n   ``\'utf-8\'``. *errors* may be given to set a different error\n   handling scheme.  The default for *errors* is ``\'strict\'``, meaning\n   that encoding errors raise a ``UnicodeError``.  Other possible\n   values are ``\'ignore\'``, ``\'replace\'`` and any other name\n   registered via ``codecs.register_error()``, see section *Codec Base\n   Classes*. For a list of possible encodings, see section *Standard\n   Encodings*.\n\n   Changed in version 3.1: Added support for keyword arguments.\n\nThe bytes and bytearray types have an additional class method:\n\nclassmethod bytes.fromhex(string)\nclassmethod bytearray.fromhex(string)\n\n   This ``bytes`` class method returns a bytes or bytearray object,\n   decoding the given string object.  The string must contain two\n   hexadecimal digits per byte, spaces are ignored.\n\n   >>> bytes.fromhex(\'f0 f1f2  \')\n   b\'\\xf0\\xf1\\xf2\'\n\nThe maketrans and translate methods differ in semantics from the\nversions available on strings:\n\nbytes.translate(table[, delete])\nbytearray.translate(table[, delete])\n\n   Return a copy of the bytes or bytearray object where all bytes\n   occurring in the optional argument *delete* are removed, and the\n   remaining bytes have been mapped through the given translation\n   table, which must be a bytes object of length 256.\n\n   You can use the ``bytes.maketrans()`` method to create a\n   translation table.\n\n   Set the *table* argument to ``None`` for translations that only\n   delete characters:\n\n      >>> b\'read this short text\'.translate(None, b\'aeiou\')\n      b\'rd ths shrt txt\'\n\nstatic bytes.maketrans(from, to)\nstatic bytearray.maketrans(from, to)\n\n   This static method returns a translation table usable for\n   ``bytes.translate()`` that will map each character in *from* into\n   the character at the same position in *to*; *from* and *to* must be\n   bytes objects and have the same length.\n\n   New in version 3.1.\n',
+ 'typesseq': '\nSequence Types --- ``str``, ``bytes``, ``bytearray``, ``list``, ``tuple``, ``range``\n************************************************************************************\n\nThere are six sequence types: strings, byte sequences (``bytes``\nobjects), byte arrays (``bytearray`` objects), lists, tuples, and\nrange objects.  For other containers see the built in ``dict`` and\n``set`` classes, and the ``collections`` module.\n\nStrings contain Unicode characters.  Their literals are written in\nsingle or double quotes: ``\'xyzzy\'``, ``"frobozz"``.  See *String and\nBytes literals* for more about string literals.  In addition to the\nfunctionality described here, there are also string-specific methods\ndescribed in the *String Methods* section.\n\nBytes and bytearray objects contain single bytes -- the former is\nimmutable while the latter is a mutable sequence. Bytes objects can be\nconstructed by using the constructor, ``bytes()``, and from literals;\nuse a ``b`` prefix with normal string syntax: ``b\'xyzzy\'``.  To\nconstruct byte arrays, use the ``bytearray()`` function.\n\nWhile string objects are sequences of characters (represented by\nstrings of length 1), bytes and bytearray objects are sequences of\n*integers* (between 0 and 255), representing the ASCII value of single\nbytes.  That means that for a bytes or bytearray object *b*, ``b[0]``\nwill be an integer, while ``b[0:1]`` will be a bytes or bytearray\nobject of length 1.  The representation of bytes objects uses the\nliteral format (``b\'...\'``) since it is generally more useful than\ne.g. ``bytes([50, 19, 100])``.  You can always convert a bytes object\ninto a list of integers using ``list(b)``.\n\nAlso, while in previous Python versions, byte strings and Unicode\nstrings could be exchanged for each other rather freely (barring\nencoding issues), strings and bytes are now completely separate\nconcepts.  There\'s no implicit en-/decoding if you pass an object of\nthe wrong type.  A string always compares unequal to a bytes or\nbytearray object.\n\nLists are constructed with square brackets, separating items with\ncommas: ``[a, b, c]``.  Tuples are constructed by the comma operator\n(not within square brackets), with or without enclosing parentheses,\nbut an empty tuple must have the enclosing parentheses, such as ``a,\nb, c`` or ``()``.  A single item tuple must have a trailing comma,\nsuch as ``(d,)``.\n\nObjects of type range are created using the ``range()`` function.\nThey don\'t support concatenation or repetition, and using ``min()`` or\n``max()`` on them 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*, *j* and *k* 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(i)``     | index of the first occurence of  |            |\n|                    | *i* in *s*                       |            |\n+--------------------+----------------------------------+------------+\n| ``s.count(i)``     | total number of occurences of    |            |\n|                    | *i* 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\ncompare equal and the two sequences must be of the same type and have\nthe same length.  (For full details see *Comparisons* in the language\nreference.)\n\nNotes:\n\n1. When *s* is a string object, the ``in`` and ``not in`` operations\n   act like a substring test.\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. Concatenating immutable strings always results in a new object.\n   This means that building up a string by repeated concatenation will\n   have a quadratic runtime cost in the total string length.  To get a\n   linear runtime cost, you must switch to one of the alternatives\n   below:\n\n   * if concatenating ``str`` objects, you can build a list and use\n     ``str.join()`` at the end;\n\n   * if concatenating ``bytes`` objects, you can similarly use\n     ``bytes.join()``, or you can do in-place concatenation with a\n     ``bytearray`` object.  ``bytearray`` objects are mutable and have\n     an efficient overallocation mechanism.\n\n\nString Methods\n==============\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n   Return a copy of the string with its first character capitalized\n   and the rest lowercased.\n\nstr.casefold()\n\n   Return a casefolded copy of the string. Casefolded strings may be\n   used for caseless matching.\n\n   Casefolding is similar to lowercasing but more aggressive because\n   it is intended to remove all case distinctions in a string. For\n   example, the German lowercase letter ``\'\xc3\x9f\'`` is equivalent to\n   ``"ss"``. Since it is already lowercase, ``lower()`` would do\n   nothing to ``\'\xc3\x9f\'``; ``casefold()`` converts it to ``"ss"``.\n\n   The casefolding algorithm is described in section 3.13 of the\n   Unicode Standard.\n\n   New in version 3.3.\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\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.encode(encoding="utf-8", errors="strict")\n\n   Return an encoded version of the string as a bytes object. Default\n   encoding is ``\'utf-8\'``. *errors* may be given to set a different\n   error handling scheme. The default for *errors* is ``\'strict\'``,\n   meaning that encoding errors raise a ``UnicodeError``. Other\n   possible values are ``\'ignore\'``, ``\'replace\'``,\n   ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n   registered via ``codecs.register_error()``, see section *Codec Base\n   Classes*. For a list of possible encodings, see section *Standard\n   Encodings*.\n\n   Changed in version 3.1: 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\nstr.expandtabs([tabsize])\n\n   Return a copy of the string where all tab characters are replaced\n   by zero or more spaces, depending on the current column and the\n   given tab size.  The column number is reset to zero after each\n   newline occurring in the string. If *tabsize* is not given, a tab\n   size of ``8`` characters is assumed.  This doesn\'t understand other\n   non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n   Return the lowest index in the string where substring *sub* is\n   found, such that *sub* is contained in the slice ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` if *sub* is not found.\n\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\nstr.format_map(mapping)\n\n   Similar to ``str.format(**mapping)``, except that ``mapping`` is\n   used directly and not copied to a ``dict`` .  This is useful if for\n   example ``mapping`` is a dict subclass:\n\n   >>> class Default(dict):\n   ...     def __missing__(self, key):\n   ...         return key\n   ...\n   >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n   \'Guido was born in country\'\n\n   New in version 3.2.\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.  A character\n   ``c`` is alphanumeric if one of the following returns ``True``:\n   ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n   ``c.isnumeric()``.\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.  Alphabetic\n   characters are those characters defined in the Unicode character\n   database as "Letter", i.e., those with general category property\n   being one of "Lm", "Lt", "Lu", "Ll", or "Lo".  Note that this is\n   different from the "Alphabetic" property defined in the Unicode\n   Standard.\n\nstr.isdecimal()\n\n   Return true if all characters in the string are decimal characters\n   and there is at least one character, false otherwise. Decimal\n   characters are those from general category "Nd". This category\n   includes digit characters, and all characters that can be used to\n   form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\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.  Digits include decimal\n   characters and digits that need special handling, such as the\n   compatibility superscript digits.  Formally, a digit is a character\n   that has the property value Numeric_Type=Digit or\n   Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n   Return true if the string is a valid identifier according to the\n   language definition, section *Identifiers and keywords*.\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\nstr.isnumeric()\n\n   Return true if all characters in the string are numeric characters,\n   and there is at least one character, false otherwise. Numeric\n   characters include digit characters, and all characters that have\n   the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n   ONE FIFTH.  Formally, numeric characters are those with the\n   property value Numeric_Type=Digit, Numeric_Type=Decimal or\n   Numeric_Type=Numeric.\n\nstr.isprintable()\n\n   Return true if all characters in the string are printable or the\n   string is empty, false otherwise.  Nonprintable characters are\n   those characters defined in the Unicode character database as\n   "Other" or "Separator", excepting the ASCII space (0x20) which is\n   considered printable.  (Note that printable characters in this\n   context are those which should not be escaped when ``repr()`` is\n   invoked on a string.  It has no bearing on the handling of strings\n   written to ``sys.stdout`` or ``sys.stderr``.)\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.  Whitespace\n   characters  are those characters defined in the Unicode character\n   database as "Other" or "Separator" and those with bidirectional\n   property being one of "WS", "B", or "S".\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\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\nstr.join(iterable)\n\n   Return a string which is the concatenation of the strings in the\n   *iterable* *iterable*.  A ``TypeError`` will be raised if there are\n   any non-string values in *iterable*, including ``bytes`` objects.\n   The separator between elements is the 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\nstr.lower()\n\n   Return a copy of the string with all the cased characters [4]\n   converted to lowercase.\n\n   The lowercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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\nstatic str.maketrans(x[, y[, z]])\n\n   This static method returns a translation table usable for\n   ``str.translate()``.\n\n   If there is only one argument, it must be a dictionary mapping\n   Unicode ordinals (integers) or characters (strings of length 1) to\n   Unicode ordinals, strings (of arbitrary lengths) or None.\n   Character keys will then be converted to ordinals.\n\n   If there are two arguments, they must be strings of equal length,\n   and in the resulting dictionary, each character in x will be mapped\n   to the character at the same position in y.  If there is a third\n   argument, it must be a string, whose characters will be mapped to\n   None in the result.\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\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\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\nstr.rsplit(sep=None, maxsplit=-1)\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\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\nstr.split(sep=None, maxsplit=-1)\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\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\nstr.swapcase()\n\n   Return a copy of the string with uppercase characters converted to\n   lowercase and vice versa. Note that it is not necessarily true that\n   ``s.swapcase().swapcase() == s``.\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\nstr.translate(map)\n\n   Return a copy of the *s* where all characters have been mapped\n   through the *map* which must be a dictionary of Unicode ordinals\n   (integers) to Unicode ordinals, strings or ``None``.  Unmapped\n   characters are left untouched. Characters mapped to ``None`` are\n   deleted.\n\n   You can use ``str.maketrans()`` to create a translation map from\n   character-to-character mappings in different formats.\n\n   Note: An even more flexible approach is to create a custom character\n     mapping codec using the ``codecs`` module (see\n     ``encodings.cp1251`` 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   The uppercasing algorithm used is described in section 3.13 of the\n   Unicode Standard.\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\nOld String Formatting Operations\n================================\n\nNote: The formatting operations described here are modelled on C\'s\n  printf() syntax.  They only support formatting of certain builtin\n  types.  The use of a binary operator means that care may be needed\n  in order to format tuples and dictionaries correctly.  As the new\n  *String Formatting* syntax is more flexible and handles tuples and\n  dictionaries naturally, it is recommended for new code.  However,\n  there are no current plans to deprecate printf-style formatting.\n\nString objects have one unique built-in operation: the ``%`` operator\n(modulo). This is also known as the string *formatting* or\n*interpolation* operator. Given ``format % values`` (where *format* is\na string), ``%`` conversion specifications in *format* are replaced\nwith zero or more elements of *values*. The effect is similar to the\nusing ``sprintf()`` in the C language.\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\n   precision is read from the next element of the tuple in *values*,\n   and the 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()``).  | (5)     |\n+--------------+-------------------------------------------------------+---------+\n| ``\'a\'``      | String (converts any Python object using              | (5)     |\n|              | ``ascii()``).                                         |         |\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. If precision is ``N``, the output is truncated to ``N`` characters.\n\n1. 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 3.1: ``%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\nRange Type\n==========\n\nThe ``range`` type is an immutable sequence which is commonly used for\nlooping.  The advantage of the ``range`` type is that an ``range``\nobject will always take the same amount of memory, no matter the size\nof the range it represents.\n\nRange objects have relatively little behavior: they support indexing,\ncontains, iteration, the ``len()`` function, and the following\nmethods:\n\nrange.count(x)\n\n   Return the number of *i*\'s for which ``s[i] == x``.\n\n   New in version 3.2.\n\nrange.index(x)\n\n   Return the smallest *i* such that ``s[i] == x``.  Raises\n   ``ValueError`` when *x* is not in the range.\n\n   New in version 3.2.\n\n\nMutable Sequence Types\n======================\n\nList and bytearray objects support additional operations that allow\nin-place modification of the object.  Other mutable sequence types\n(when added to the language) should also support these operations.\nStrings and tuples are immutable sequence types: such objects cannot\nbe modified once created. The following operations are defined on\nmutable sequence types (where *x* is an arbitrary object).\n\nNote that while lists allow their items to be of any type, bytearray\nobject "items" are all integers in the range 0 <= x < 256.\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)] =     |                       |\n|                                | [x]``                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (2)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.clear()``                  | remove all items from ``s``      |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.copy()``                   | return a shallow copy of ``s``   |                       |\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    | (3)                   |\n|                                | ``s[k] == x`` and ``i <= k < j`` |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (4)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (5)                   |\n|                                | return x``                       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (3)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()``                | reverses the items of *s* in     | (6)                   |\n|                                | place                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([key[, reverse]])``   | sort the items of *s* in place   | (6), (7), (8)         |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. *x* can be any iterable object.\n\n3. 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 sequence length is added, as for slice indices.  If it\n   is still negative, it is truncated to zero, as for slice indices.\n\n4. When a negative index is passed as the first parameter to the\n   ``insert()`` method, the sequence length is added, as for slice\n   indices.  If it is still negative, it is truncated to zero, as for\n   slice indices.\n\n5. The optional argument *i* defaults to ``-1``, so that by default\n   the last item is removed and returned.\n\n6. The ``sort()`` and ``reverse()`` methods modify the sequence in\n   place for economy of space when sorting or reversing a large\n   sequence.  To remind you that they operate by side effect, they\n   don\'t return the sorted or reversed sequence.\n\n7. The ``sort()`` method takes optional arguments for controlling the\n   comparisons.  Each must be specified as a keyword argument.\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``. Use ``functools.cmp_to_key()`` to\n   convert an old-style *cmp* function to a *key* function.\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   The ``sort()`` method is guaranteed to be stable.  A sort is stable\n   if it guarantees not to change the relative order of elements that\n   compare equal --- this is helpful for sorting in multiple passes\n   (for example, sort by department, then by salary grade).\n\n   **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 makes the list appear\n   empty for the duration, and raises ``ValueError`` if it can detect\n   that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\n\n      New in version 3.3: ``clear()`` and ``copy()`` methods.\n\n\nBytes and Byte Array Methods\n============================\n\nBytes and bytearray objects, being "strings of bytes", have all\nmethods found on strings, with the exception of ``encode()``,\n``format()`` and ``isidentifier()``, which do not make sense with\nthese types.  For converting the objects to strings, they have a\n``decode()`` method.\n\nWherever one of these methods needs to interpret the bytes as\ncharacters (e.g. the ``is...()`` methods), the ASCII character set is\nassumed.\n\nNew in version 3.3: The functions ``count()``, ``find()``,\n``index()``, ``rfind()`` and ``rindex()`` have additional semantics\ncompared to the corresponding string functions: They also accept an\ninteger in range 0 to 255 (a byte) as their first argument.\n\nNote: The methods on bytes and bytearray objects don\'t accept strings as\n  their arguments, just as the methods on strings don\'t accept bytes\n  as their arguments.  For example, you have to write\n\n     a = "abc"\n     b = a.replace("a", "f")\n\n  and\n\n     a = b"abc"\n     b = a.replace(b"a", b"f")\n\nbytes.decode(encoding="utf-8", errors="strict")\nbytearray.decode(encoding="utf-8", errors="strict")\n\n   Return a string decoded from the given bytes.  Default encoding is\n   ``\'utf-8\'``. *errors* may be given to set a different error\n   handling scheme.  The default for *errors* is ``\'strict\'``, meaning\n   that encoding errors raise a ``UnicodeError``.  Other possible\n   values are ``\'ignore\'``, ``\'replace\'`` and any other name\n   registered via ``codecs.register_error()``, see section *Codec Base\n   Classes*. For a list of possible encodings, see section *Standard\n   Encodings*.\n\n   Changed in version 3.1: Added support for keyword arguments.\n\nThe bytes and bytearray types have an additional class method:\n\nclassmethod bytes.fromhex(string)\nclassmethod bytearray.fromhex(string)\n\n   This ``bytes`` class method returns a bytes or bytearray object,\n   decoding the given string object.  The string must contain two\n   hexadecimal digits per byte, spaces are ignored.\n\n   >>> bytes.fromhex(\'f0 f1f2  \')\n   b\'\\xf0\\xf1\\xf2\'\n\nThe maketrans and translate methods differ in semantics from the\nversions available on strings:\n\nbytes.translate(table[, delete])\nbytearray.translate(table[, delete])\n\n   Return a copy of the bytes or bytearray object where all bytes\n   occurring in the optional argument *delete* are removed, and the\n   remaining bytes have been mapped through the given translation\n   table, which must be a bytes object of length 256.\n\n   You can use the ``bytes.maketrans()`` method to create a\n   translation table.\n\n   Set the *table* argument to ``None`` for translations that only\n   delete characters:\n\n      >>> b\'read this short text\'.translate(None, b\'aeiou\')\n      b\'rd ths shrt txt\'\n\nstatic bytes.maketrans(from, to)\nstatic bytearray.maketrans(from, to)\n\n   This static method returns a translation table usable for\n   ``bytes.translate()`` that will map each character in *from* into\n   the character at the same position in *to*; *from* and *to* must be\n   bytes objects and have the same length.\n\n   New in version 3.1.\n',
  'typesseq-mutable': '\nMutable Sequence Types\n**********************\n\nList and bytearray objects support additional operations that allow\nin-place modification of the object.  Other mutable sequence types\n(when added to the language) should also support these operations.\nStrings and tuples are immutable sequence types: such objects cannot\nbe modified once created. The following operations are defined on\nmutable sequence types (where *x* is an arbitrary object).\n\nNote that while lists allow their items to be of any type, bytearray\nobject "items" are all integers in the range 0 <= x < 256.\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)] =     |                       |\n|                                | [x]``                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (2)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.clear()``                  | remove all items from ``s``      |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.copy()``                   | return a shallow copy of ``s``   |                       |\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    | (3)                   |\n|                                | ``s[k] == x`` and ``i <= k < j`` |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (4)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (5)                   |\n|                                | return x``                       |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (3)                   |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()``                | reverses the items of *s* in     | (6)                   |\n|                                | place                            |                       |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([key[, reverse]])``   | sort the items of *s* in place   | (6), (7), (8)         |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. *x* can be any iterable object.\n\n3. 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 sequence length is added, as for slice indices.  If it\n   is still negative, it is truncated to zero, as for slice indices.\n\n4. When a negative index is passed as the first parameter to the\n   ``insert()`` method, the sequence length is added, as for slice\n   indices.  If it is still negative, it is truncated to zero, as for\n   slice indices.\n\n5. The optional argument *i* defaults to ``-1``, so that by default\n   the last item is removed and returned.\n\n6. The ``sort()`` and ``reverse()`` methods modify the sequence in\n   place for economy of space when sorting or reversing a large\n   sequence.  To remind you that they operate by side effect, they\n   don\'t return the sorted or reversed sequence.\n\n7. The ``sort()`` method takes optional arguments for controlling the\n   comparisons.  Each must be specified as a keyword argument.\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``. Use ``functools.cmp_to_key()`` to\n   convert an old-style *cmp* function to a *key* function.\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   The ``sort()`` method is guaranteed to be stable.  A sort is stable\n   if it guarantees not to change the relative order of elements that\n   compare equal --- this is helpful for sorting in multiple passes\n   (for example, sort by department, then by salary grade).\n\n   **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 makes the list appear\n   empty for the duration, and raises ``ValueError`` if it can detect\n   that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\n\n      New in version 3.3: ``clear()`` and ``copy()`` methods.\n',
  'unary': '\nUnary arithmetic and bitwise operations\n***************************************\n\nAll unary arithmetic and bitwise operations have the same priority:\n\n   u_expr ::= power | "-" u_expr | "+" u_expr | "~" u_expr\n\nThe unary ``-`` (minus) operator yields the negation of its numeric\nargument.\n\nThe unary ``+`` (plus) operator yields its numeric argument unchanged.\n\nThe unary ``~`` (invert) operator yields the bitwise inversion of its\ninteger argument.  The bitwise inversion of ``x`` is defined as\n``-(x+1)``.  It only applies to integral numbers.\n\nIn all three cases, if the argument does not have the proper type, a\n``TypeError`` exception is raised.\n',
  'while': '\nThe ``while`` statement\n***********************\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n   while_stmt ::= "while" expression ":" suite\n                  ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite.  A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n',