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| -rw-r--r-- | Lib/pydoc_data/topics.py | 12 |
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diff --git a/Lib/pydoc_data/topics.py b/Lib/pydoc_data/topics.py index 3328f68..dcb2f4b 100644 --- a/Lib/pydoc_data/topics.py +++ b/Lib/pydoc_data/topics.py @@ -1,4 +1,4 @@ -# Autogenerated by Sphinx on Sat May 30 10:41:05 2009 +# Autogenerated by Sphinx on Sat Jun 13 08:08:53 2009 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. (This rule is relaxed as of\n Python 1.5; in earlier versions, the object had to be a tuple.\n Since strings are sequences, an assignment like ``a, b = "xy"`` is\n now legal as long as the string has the right length.)\n\n * If the target list contains one target prefixed with an asterisk,\n called a "starred" target: The object must be a sequence with at\n least as many items as there are targets in the target list, minus\n one. The first items of the sequence are assigned, from left to\n right, to the targets before the starred target. The final items\n of the sequence are assigned to the targets after the starred\n target. A list of the remaining items in the sequence is then\n assigned to the starred target (the list can be empty).\n\n * Else: The object must be a sequence with the same number of items\n as there are targets in the target list, and the items are\n assigned, from left to right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n * If the name does not occur in a ``global`` or ``nonlocal``\n statement in the current code block: the name is bound to the\n object in the current local namespace.\n\n * Otherwise: the name is bound to the object in the global namespace\n or the outer namespace determined by ``nonlocal``, respectively.\n\n The name is rebound if it was already bound. This may cause the\n reference count for the object previously bound to the name to reach\n zero, causing the object to be deallocated and its destructor (if it\n has one) to be called.\n\n The name is rebound if it was already bound. This may cause the\n reference count for the object previously bound to the name to reach\n zero, causing the object to be deallocated and its destructor (if it\n has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in square\n brackets: The object must be 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* If the target is a subscription: The primary expression in the\n reference is evaluated. It should yield either a mutable sequence\n object (such as a list) or a mapping object (such as a dictionary).\n Next, the subscript expression is evaluated.\n\n If the primary is a mutable sequence object (such as a list), the\n subscript must yield an integer. If it is negative, the sequence\'s\n length is added to it. The resulting value must be a nonnegative\n integer less than the sequence\'s length, and the sequence is asked\n to assign the assigned object to its item with that index. If the\n index is out of range, ``IndexError`` is raised (assignment to a\n subscripted sequence cannot add new items to a list).\n\n If the primary is a mapping object (such as a dictionary), the\n subscript must have a type compatible with the mapping\'s key type,\n and the mapping is then asked to create a key/datum pair which maps\n the subscript to the assigned object. This can either replace an\n existing key/value pair with the same key value, or insert a new\n key/value pair (if no key with the same value existed).\n\n For user-defined objects, the ``__setitem__()`` method is called\n with appropriate arguments.\n\n* If the target is a slicing: The primary expression in the reference\n is evaluated. It should yield a mutable sequence object (such as a\n list). The assigned object should be a sequence object of the same\n type. Next, the lower and upper bound expressions are evaluated,\n insofar they are present; defaults are zero and the sequence\'s\n length. The bounds should evaluate to integers. If either bound is\n negative, the sequence\'s length is added to it. The resulting\n bounds are clipped to lie between zero and the sequence\'s length,\n inclusive. Finally, the sequence object is asked to replace the\n slice with the items of the assigned sequence. The length of the\n slice may be different from the length of the assigned sequence,\n thus changing the length of the target sequence, if the object\n allows it.\n\n(In the current implementation, the syntax for targets is taken to be\nthe same as for expressions, and invalid syntax is rejected during the\ncode generation phase, causing less detailed error messages.)\n\nWARNING: Although the definition of assignment implies that overlaps\nbetween the left-hand side and the right-hand side are \'safe\' (for\nexample ``a, b = b, a`` swaps two variables), overlaps *within* the\ncollection of assigned-to variables are not safe! For instance, the\nfollowing program prints ``[0, 2]``:\n\n x = [0, 1]\n i = 0\n i, x[i] = 1, 2\n print(x)\n\nSee also:\n\n **PEP 3132** - Extended Iterable Unpacking\n The specification for the ``*target`` feature.\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= 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 initial value is\nretrieved with a ``getattr()`` and the result is assigned with a\n``setattr()``. Notice that the two methods do not necessarily refer\nto the same variable. When ``getattr()`` refers to a class variable,\n``setattr()`` still writes to an instance variable. For example:\n\n class A:\n x = 3 # class variable\n a = A()\n a.x += 1 # writes a.x as 4 leaving A.x as 3\n', 'atom-identifiers': '\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name. See section\n*Identifiers and keywords* for lexical definition and section *Naming\nand binding* for documentation of naming and binding.\n\nWhen the name is bound to an object, evaluation of the atom yields\nthat object. When a name is not bound, an attempt to evaluate it\nraises a ``NameError`` exception.\n\n**Private name mangling:** When an identifier that textually occurs in\na class definition begins with two or more underscore characters and\ndoes not end in two or more underscores, it is considered a *private\nname* of that class. Private names are transformed to a longer form\nbefore code is generated for them. The transformation inserts the\nclass name in front of the name, with leading underscores removed, and\na single underscore inserted in front of the class name. For example,\nthe identifier ``__spam`` occurring in a class named ``Ham`` will be\ntransformed to ``_Ham__spam``. This transformation is independent of\nthe syntactical context in which the identifier is used. If the\ntransformed name is extremely long (longer than 255 characters),\nimplementation defined truncation may happen. If the class name\nconsists only of underscores, no transformation is done.\n', @@ -19,7 +19,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss 'calls': '\nCalls\n*****\n\nA call calls a callable object (e.g., a function) with a possibly\nempty series of arguments:\n\n call ::= primary "(" [argument_list [","] | comprehension] ")"\n argument_list ::= positional_arguments ["," keyword_arguments]\n ["," "*" expression] ["," keyword_arguments]\n ["," "**" expression]\n | keyword_arguments ["," "*" expression]\n ["," keyword_arguments] ["," "**" expression]\n | "*" expression ["," keyword_arguments] ["," "**" expression]\n | "**" expression\n positional_arguments ::= expression ("," expression)*\n keyword_arguments ::= keyword_item ("," keyword_item)*\n keyword_item ::= identifier "=" expression\n\nA trailing comma may be present after the positional and keyword\narguments but does not affect the semantics.\n\nThe primary must evaluate to a callable object (user-defined\nfunctions, built-in functions, methods of built-in objects, class\nobjects, methods of class instances, and all objects having a\n``__call__()`` method are callable). All argument expressions are\nevaluated before the call is attempted. Please refer to section\n*Function definitions* for the syntax of formal parameter lists.\n\nIf keyword arguments are present, they are first converted to\npositional arguments, as follows. First, a list of unfilled slots is\ncreated for the formal parameters. If there are N positional\narguments, they are placed in the first N slots. Next, for each\nkeyword argument, the identifier is used to determine the\ncorresponding slot (if the identifier is the same as the first formal\nparameter name, the first slot is used, and so on). If the slot is\nalready filled, a ``TypeError`` exception is raised. Otherwise, the\nvalue of the argument is placed in the slot, filling it (even if the\nexpression is ``None``, it fills the slot). When all arguments have\nbeen processed, the slots that are still unfilled are filled with the\ncorresponding default value from the function definition. (Default\nvalues are calculated, once, when the function is defined; thus, a\nmutable object such as a list or dictionary used as default value will\nbe shared by all calls that don\'t specify an argument value for the\ncorresponding slot; this should usually be avoided.) If there are any\nunfilled slots for which no default value is specified, a\n``TypeError`` exception is raised. Otherwise, the list of filled\nslots is used as the argument list for the call.\n\nNote: An implementation may provide builtin functions whose positional\n parameters do not have names, even if they are \'named\' for the\n purpose of documentation, and which therefore cannot be supplied by\n keyword. In CPython, this is the case for functions implemented in\n C that use ``PyArg_ParseTuple()`` to parse their arguments.\n\nIf there are more positional arguments than there are formal parameter\nslots, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``*identifier`` is present; in this case, that formal\nparameter receives a tuple containing the excess positional arguments\n(or an empty tuple if there were no excess positional arguments).\n\nIf any keyword argument does not correspond to a formal parameter\nname, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``**identifier`` is present; in this case, that\nformal parameter receives a dictionary containing the excess keyword\narguments (using the keywords as keys and the argument values as\ncorresponding values), or a (new) empty dictionary if there were no\nexcess keyword arguments.\n\nIf the syntax ``*expression`` appears in the function call,\n``expression`` must evaluate to a sequence. Elements from this\nsequence are treated as if they were additional positional arguments;\nif there are positional arguments *x1*,..., *xN*, and ``expression``\nevaluates to a sequence *y1*, ..., *yM*, this is equivalent to a call\nwith M+N positional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.\n\nA consequence of this is that although the ``*expression`` syntax may\nappear *after* some keyword arguments, it is processed *before* the\nkeyword arguments (and the ``**expression`` argument, if any -- see\nbelow). So:\n\n >>> def f(a, b):\n ... print(a, b)\n ...\n >>> f(b=1, *(2,))\n 2 1\n >>> f(a=1, *(2,))\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n TypeError: f() got multiple values for keyword argument \'a\'\n >>> f(1, *(2,))\n 1 2\n\nIt is unusual for both keyword arguments and the ``*expression``\nsyntax to be used in the same call, so in practice this confusion does\nnot arise.\n\nIf the syntax ``**expression`` appears in the function call,\n``expression`` must evaluate to a mapping, the contents of which are\ntreated as additional keyword arguments. In the case of a keyword\nappearing in both ``expression`` and as an explicit keyword argument,\na ``TypeError`` exception is raised.\n\nFormal parameters using the syntax ``*identifier`` or ``**identifier``\ncannot be used as positional argument slots or as keyword argument\nnames.\n\nA call always returns some value, possibly ``None``, unless it raises\nan exception. How this value is computed depends on the type of the\ncallable object.\n\nIf it is---\n\na user-defined function:\n The code block for the function is executed, passing it the\n argument list. The first thing the code block will do is bind the\n formal parameters to the arguments; this is described in section\n *Function definitions*. When the code block executes a ``return``\n statement, this specifies the return value of the function call.\n\na built-in function or method:\n The result is up to the interpreter; see *Built-in Functions* for\n the descriptions of built-in functions and methods.\n\na class object:\n A new instance of that class is returned.\n\na class instance method:\n The corresponding user-defined function is called, with an argument\n list that is one longer than the argument list of the call: the\n instance becomes the first argument.\n\na class instance:\n The class must define a ``__call__()`` method; the effect is then\n the same as if that method was called.\n', 'class': '\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [expression_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. It first evaluates the\ninheritance list, if present. Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing. The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.) When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary. The class name is bound to this class object in the\noriginal local namespace.\n\nClasses can also be decorated; as with functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``. Both class and\ninstance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results. Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n **PEP 3129** - Class Decorators\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions. The evaluation rules for the decorator\nexpressions are the same as for functions. The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n', 'comparisons': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects. The objects need not have the same type.\nIf both are numbers, they are converted to a common type. Otherwise,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes. You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n are identical to themselves, ``x is x`` but are not equal to\n themselves, ``x != x``. Additionally, comparing any value to a\n not-a-number value will return ``False``. For example, both ``3 <\n float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``[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 their sorted\n ``(key, value)`` lists compare equal. [4] Outcomes other than\n equality are resolved consistently, but are not otherwise defined.\n [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, ``min()``, ``max()``, and ``sorted()`` produce\n undefined results given a list of sets as inputs.\n\n* Most other objects of builtin types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison. Most\nnumeric types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is. When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``. This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons. For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership. ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise. ``x\nnot in s`` returns the negation of ``x in s``. All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` is equivalent to ``any(x is e or x == e for val\ne in y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` and do\ndefine ``__getitem__()``, ``x in y`` is true if and only if there is a\nnon-negative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [6]\n', - 'compound': '\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs. ``try`` specifies exception handlers and/or\ncleanup code for a group of statements, while the ``with`` statement\nallows the execution of initialization and finalization code around a\nblock of code. Function and class definitions are also syntactically\ncompound statements.\n\nCompound statements consist of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n if test1: if test2: print(x)\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print()`` calls are executed:\n\n if x < y < z: print(x); print(y); print(z)\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe ``try`` statement\n=====================\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n N = None\n del N\n\nThat means that you have to assign the exception to a different name\nif you want to be able to refer to it after the except clause. The\nreason for this is that with the traceback attached to them,\nexceptions will form a reference cycle with the stack frame, keeping\nall locals in that frame alive until the next garbage collection\noccurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting\nof: ``exc_type``, the exception class; ``exc_value``, the exception\ninstance; ``exc_traceback``, a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. ``sys.exc_info()`` values are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost. The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the ``with`` statement with one "item" proceeds as\nfollows:\n\n1. The context expression is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__enter__()`` method is invoked.\n\n3. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 5 below.\n\n4. The suite is executed.\n\n5. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [expression_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. It first evaluates the\ninheritance list, if present. Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing. The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.) When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary. The class name is bound to this class object in the\noriginal local namespace.\n\nClasses can also be decorated; as with functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``. Both class and\ninstance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results. Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n **PEP 3129** - Class Decorators\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions. The evaluation rules for the decorator\nexpressions are the same as for functions. The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n', + 'compound': '\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs. ``try`` specifies exception handlers and/or\ncleanup code for a group of statements, while the ``with`` statement\nallows the execution of initialization and finalization code around a\nblock of code. Function and class definitions are also syntactically\ncompound statements.\n\nCompound statements consist of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n if test1: if test2: print(x)\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print()`` calls are executed:\n\n if x < y < z: print(x); print(y); print(z)\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``list(range(3))`` returns the list ``[0, 1,\n2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe ``try`` statement\n=====================\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n N = None\n del N\n\nThat means that you have to assign the exception to a different name\nif you want to be able to refer to it after the except clause. The\nreason for this is that with the traceback attached to them,\nexceptions will form a reference cycle with the stack frame, keeping\nall locals in that frame alive until the next garbage collection\noccurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting\nof: ``exc_type``, the exception class; ``exc_value``, the exception\ninstance; ``exc_traceback``, a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. ``sys.exc_info()`` values are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost. The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the ``with`` statement with one "item" proceeds as\nfollows:\n\n1. The context expression is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__enter__()`` method is invoked.\n\n3. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 5 below.\n\n4. The suite is executed.\n\n5. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [expression_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. It first evaluates the\ninheritance list, if present. Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing. The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.) When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary. The class name is bound to this class object in the\noriginal local namespace.\n\nClasses can also be decorated; as with functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``. Both class and\ninstance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results. Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n **PEP 3129** - Class Decorators\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions. The evaluation rules for the decorator\nexpressions are the same as for functions. The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n', 'context-managers': '\nWith Statement Context Managers\n*******************************\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code. Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The ``with``\n statement will bind this method\'s return value to the target(s)\n specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be ``None``.\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that ``__exit__()`` methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n', 'continue': '\nThe ``continue`` statement\n**************************\n\n continue_stmt ::= "continue"\n\n``continue`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition or\n``finally`` clause within that loop. It continues with the next cycle\nof the nearest enclosing loop.\n\nWhen ``continue`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nstarting the next loop cycle.\n', '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', @@ -33,7 +33,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss 'execmodel': '\nExecution model\n***************\n\n\nNaming and binding\n==================\n\n*Names* refer to objects. Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block. A script\nfile (a file given as standard input to the interpreter or specified\non the interpreter command line the first argument) is a code block.\nA script command (a command specified on the interpreter command line\nwith the \'**-c**\' option) is a code block. The string argument passed\nto the built-in functions ``eval()`` and ``exec()`` is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes comprehensions and generator\nexpressions since they are implemented using a function scope. This\nmeans that the following will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nIf a name is bound in a block, it is a local variable of that block,\nunless declared as ``nonlocal``. If a name is bound at the module\nlevel, it is a global variable. (The variables of the module code\nblock are local and global.) If a variable is used in a code block\nbut not defined there, it is a *free variable*.\n\nWhen a name is not found at all, a ``NameError`` exception is raised.\nIf the name refers to a local variable that has not been bound, a\n``UnboundLocalError`` exception is raised. ``UnboundLocalError`` is a\nsubclass of ``NameError``.\n\nThe following constructs bind names: formal parameters to functions,\n``import`` statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, ``for`` loop header, or\nafter ``as`` in a ``with`` statement or :keyword.`except` clause. The\n``import`` statement of the form ``from ... import *`` binds all names\ndefined in the imported module, except those beginning with an\nunderscore. This form may only be used at the module level.\n\nA target occurring in a ``del`` statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name). It\nis illegal to unbind a name that is referenced by an enclosing scope;\nthe compiler will report a ``SyntaxError``.\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the ``global`` statement occurs within a block, all uses of the\nname specified in the statement refer to the binding of that name in\nthe top-level namespace. Names are resolved in the top-level\nnamespace by searching the global namespace, i.e. the namespace of the\nmodule containing the code block, and the builtin namespace, the\nnamespace of the module ``builtins``. The global namespace is\nsearched first. If the name is not found there, the builtin namespace\nis searched. The global statement must precede all uses of the name.\n\nThe built-in namespace associated with the execution of a code block\nis actually found by looking up the name ``__builtins__`` in its\nglobal namespace; this should be a dictionary or a module (in the\nlatter case the module\'s dictionary is used). By default, when in the\n``__main__`` module, ``__builtins__`` is the built-in module\n``builtins``; when in any other module, ``__builtins__`` is an alias\nfor the dictionary of the ``builtins`` module itself.\n``__builtins__`` can be set to a user-created dictionary to create a\nweak form of restricted execution.\n\nNote: Users should not touch ``__builtins__``; it is strictly an\n implementation detail. Users wanting to override values in the\n built-in namespace should ``import`` the ``builtins`` module and\n modify its attributes appropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n``__main__``.\n\nThe global statement has the same scope as a name binding operation in\nthe same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\nInteraction with dynamic features\n---------------------------------\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- ``import *`` --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a ``SyntaxError``.\n\nThe ``eval()`` and ``exec()`` functions do not have access to the full\nenvironment for resolving names. Names may be resolved in the local\nand global namespaces of the caller. Free variables are not resolved\nin the nearest enclosing namespace, but in the global namespace. [1]\nThe ``exec()`` and ``eval()`` functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n\n\nExceptions\n==========\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the ``raise`` statement. Exception\nhandlers are specified with the ``try`` ... ``except`` statement. The\n``finally`` clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n``SystemExit``.\n\nExceptions are identified by class instances. The ``except`` clause\nis selected depending on the class of the instance: it must reference\nthe class of the instance or a base class thereof. The instance can\nbe received by the handler and can carry additional information about\nthe exceptional condition.\n\nNote: Exception messages are not part of the Python API. Their contents\n may change from one version of Python to the next without warning\n and should not be relied on by code which will run under multiple\n versions of the interpreter.\n\nSee also the description of the ``try`` statement in section *The try\nstatement* and ``raise`` statement in section *The raise statement*.\n\n-[ Footnotes ]-\n\n[1] This limitation occurs because the code that is executed by these\n operations is not available at the time the module is compiled.\n', 'exprlists': '\nExpression lists\n****************\n\n expression_list ::= expression ( "," expression )* [","]\n\nAn expression list containing at least one comma yields a tuple. The\nlength of the tuple is the number of expressions in the list. The\nexpressions are evaluated from left to right.\n\nThe trailing comma is required only to create a single tuple (a.k.a. a\n*singleton*); it is optional in all other cases. A single expression\nwithout a trailing comma doesn\'t create a tuple, but rather yields the\nvalue of that expression. (To create an empty tuple, use an empty pair\nof parentheses: ``()``.)\n', 'floating': '\nFloating point literals\n***********************\n\nFloating point literals are described by the following lexical\ndefinitions:\n\n floatnumber ::= pointfloat | exponentfloat\n pointfloat ::= [intpart] fraction | intpart "."\n exponentfloat ::= (intpart | pointfloat) exponent\n intpart ::= digit+\n fraction ::= "." digit+\n exponent ::= ("e" | "E") ["+" | "-"] digit+\n\nNote that the integer and exponent parts are always interpreted using\nradix 10. For example, ``077e010`` is legal, and denotes the same\nnumber as ``77e10``. The allowed range of floating point literals is\nimplementation-dependent. Some examples of floating point literals:\n\n 3.14 10. .001 1e100 3.14e-10 0e0\n\nNote that numeric literals do not include a sign; a phrase like ``-1``\nis actually an expression composed of the unary operator ``-`` and the\nliteral ``1``.\n', - 'for': '\nThe ``for`` statement\n*********************\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n', + 'for': '\nThe ``for`` statement\n*********************\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``list(range(3))`` returns the list ``[0, 1,\n2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n', 'formatstrings': '\nFormat String Syntax\n********************\n\nThe ``str.format()`` method and the ``Formatter`` class share the same\nsyntax for format strings (although in the case of ``Formatter``,\nsubclasses can define their own format string syntax.)\n\nFormat strings contain "replacement fields" surrounded by curly braces\n``{}``. Anything that is not contained in braces is considered literal\ntext, which is copied unchanged to the output. If you need to include\na brace character in the literal text, it can be escaped by doubling:\n``{{`` and ``}}``.\n\nThe grammar for a replacement field is as follows:\n\n replacement_field ::= "{" field_name ["!" conversion] [":" format_spec] "}"\n field_name ::= arg_name ("." attribute_name | "[" element_index "]")*\n arg_name ::= (identifier | integer)?\n attribute_name ::= identifier\n element_index ::= integer\n conversion ::= "r" | "s" | "a"\n format_spec ::= <described in the next section>\n\nIn less formal terms, the replacement field starts with a *field_name*\nthat specifies the object whose value is to be formatted and inserted\ninto the output instead of the replacement field. The *field_name* is\noptionally followed by a *conversion* field, which is preceded by an\nexclamation point ``\'!\'``, and a *format_spec*, which is preceded by a\ncolon ``\':\'``. These specify a non-default format for the replacement\nvalue.\n\nThe *field_name* itself begins with an *arg_name* that is either\neither a number or a keyword. If it\'s a number, it refers to a\npositional argument, and if it\'s a keyword, it refers to a named\nkeyword argument. If the numerical arg_names in a format string are\n0, 1, 2, ... in sequence, they can all be omitted (not just some) and\nthe numbers 0, 1, 2, ... will be automatically inserted in that order.\nThe *arg_name* can be followed by any number of index or attribute\nexpressions. An expression of the form ``\'.name\'`` selects the named\nattribute using ``getattr()``, while an expression of the form\n``\'[index]\'`` does an index lookup using ``__getitem__()``.\n\nSome simple format string examples:\n\n "First, thou shalt count to {0}" # References first positional argument\n "Bring me a {}" # Implicitly references the first positional argument\n "From {} to {}" # Same as "From {0] to {1}"\n "My quest is {name}" # References keyword argument \'name\'\n "Weight in tons {0.weight}" # \'weight\' attribute of first positional arg\n "Units destroyed: {players[0]}" # First element of keyword argument \'players\'.\n\nThe *conversion* field causes a type coercion before formatting.\nNormally, the job of formatting a value is done by the\n``__format__()`` method of the value itself. However, in some cases\nit is desirable to force a type to be formatted as a string,\noverriding its own definition of formatting. By converting the value\nto a string before calling ``__format__()``, the normal formatting\nlogic is bypassed.\n\nThree conversion flags are currently supported: ``\'!s\'`` which calls\n``str()`` on the value, ``\'!r\'`` which calls ``repr()`` and ``\'!a\'``\nwhich calls ``ascii()``.\n\nSome examples:\n\n "Harold\'s a clever {0!s}" # Calls str() on the argument first\n "Bring out the holy {name!r}" # Calls repr() on the argument first\n\nThe *format_spec* field contains a specification of how the value\nshould be presented, including such details as field width, alignment,\npadding, decimal precision and so on. Each value type can define it\'s\nown "formatting mini-language" or interpretation of the *format_spec*.\n\nMost built-in types support a common formatting mini-language, which\nis described in the next section.\n\nA *format_spec* field can also include nested replacement fields\nwithin it. These nested replacement fields can contain only a field\nname; conversion flags and format specifications are not allowed. The\nreplacement fields within the format_spec are substituted before the\n*format_spec* string is interpreted. This allows the formatting of a\nvalue to be dynamically specified.\n\nFor example, suppose you wanted to have a replacement field whose\nfield width is determined by another variable:\n\n "A man with two {0:{1}}".format("noses", 10)\n\nThis would first evaluate the inner replacement field, making the\nformat string effectively:\n\n "A man with two {0:10}"\n\nThen the outer replacement field would be evaluated, producing:\n\n "noses "\n\nWhich is substituted into the string, yielding:\n\n "A man with two noses "\n\n(The extra space is because we specified a field width of 10, and\nbecause left alignment is the default for strings.)\n\n\nFormat Specification Mini-Language\n==================================\n\n"Format specifications" are used within replacement fields contained\nwithin a format string to define how individual values are presented\n(see *Format String Syntax*.) They can also be passed directly to the\nbuiltin ``format()`` function. Each formattable type may define how\nthe format specification is to be interpreted.\n\nMost built-in types implement the following options for format\nspecifications, although some of the formatting options are only\nsupported by the numeric types.\n\nA general convention is that an empty format string (``""``) produces\nthe same result as if you had called ``str()`` on the value.\n\nThe general form of a *standard format specifier* is:\n\n format_spec ::= [[fill]align][sign][#][0][width][.precision][type]\n fill ::= <a character other than \'}\'>\n align ::= "<" | ">" | "=" | "^"\n sign ::= "+" | "-" | " "\n width ::= integer\n precision ::= integer\n type ::= "b" | "c" | "d" | "e" | "E" | "f" | "F" | "g" | "G" | "n" | "o" | "x" | "X" | "%"\n\nThe *fill* character can be any character other than \'}\' (which\nsignifies the end of the field). The presence of a fill character is\nsignaled by the *next* character, which must be one of the alignment\noptions. If the second character of *format_spec* is not a valid\nalignment option, then it is assumed that both the fill character and\nthe alignment option are absent.\n\nThe meaning of the various alignment options is as follows:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'<\'`` | Forces the field to be left-aligned within the available |\n | | space (This is the default.) |\n +-----------+------------------------------------------------------------+\n | ``\'>\'`` | Forces the field to be right-aligned within the available |\n | | space. |\n +-----------+------------------------------------------------------------+\n | ``\'=\'`` | Forces the padding to be placed after the sign (if any) |\n | | but before the digits. This is used for printing fields |\n | | in the form \'+000000120\'. This alignment option is only |\n | | valid for numeric types. |\n +-----------+------------------------------------------------------------+\n | ``\'^\'`` | Forces the field to be centered within the available |\n | | space. |\n +-----------+------------------------------------------------------------+\n\nNote that unless a minimum field width is defined, the field width\nwill always be the same size as the data to fill it, so that the\nalignment option has no meaning in this case.\n\nThe *sign* option is only valid for number types, and can be one of\nthe following:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'+\'`` | indicates that a sign should be used for both positive as |\n | | well as negative numbers. |\n +-----------+------------------------------------------------------------+\n | ``\'-\'`` | indicates that a sign should be used only for negative |\n | | numbers (this is the default behavior). |\n +-----------+------------------------------------------------------------+\n | space | indicates that a leading space should be used on positive |\n | | numbers, and a minus sign on negative numbers. |\n +-----------+------------------------------------------------------------+\n\nThe ``\'#\'`` option is only valid for integers, and only for binary,\noctal, or hexadecimal output. If present, it specifies that the\noutput will be prefixed by ``\'0b\'``, ``\'0o\'``, or ``\'0x\'``,\nrespectively.\n\n*width* is a decimal integer defining the minimum field width. If not\nspecified, then the field width will be determined by the content.\n\nIf the *width* field is preceded by a zero (``\'0\'``) character, this\nenables zero-padding. This is equivalent to an *alignment* type of\n``\'=\'`` and a *fill* character of ``\'0\'``.\n\nThe *precision* is a decimal number indicating how many digits should\nbe displayed after the decimal point for a floating point value\nformatted with ``\'f\'`` and ``\'F\'``, or before and after the decimal\npoint for a floating point value formatted with ``\'g\'`` or ``\'G\'``.\nFor non-number types the field indicates the maximum field size - in\nother words, how many characters will be used from the field content.\nThe *precision* is not allowed for integer values.\n\nFinally, the *type* determines how the data should be presented.\n\nThe available integer presentation types are:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'b\'`` | Binary format. Outputs the number in base 2. |\n +-----------+------------------------------------------------------------+\n | ``\'c\'`` | Character. Converts the integer to the corresponding |\n | | unicode character before printing. |\n +-----------+------------------------------------------------------------+\n | ``\'d\'`` | Decimal Integer. Outputs the number in base 10. |\n +-----------+------------------------------------------------------------+\n | ``\'o\'`` | Octal format. Outputs the number in base 8. |\n +-----------+------------------------------------------------------------+\n | ``\'x\'`` | Hex format. Outputs the number in base 16, using lower- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'X\'`` | Hex format. Outputs the number in base 16, using upper- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'d\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'d\'``. |\n +-----------+------------------------------------------------------------+\n\nThe available presentation types for floating point and decimal values\nare:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'e\'`` | Exponent notation. Prints the number in scientific |\n | | notation using the letter \'e\' to indicate the exponent. |\n +-----------+------------------------------------------------------------+\n | ``\'E\'`` | Exponent notation. Same as ``\'e\'`` except it uses an upper |\n | | case \'E\' as the separator character. |\n +-----------+------------------------------------------------------------+\n | ``\'f\'`` | Fixed point. Displays the number as a fixed-point number. |\n +-----------+------------------------------------------------------------+\n | ``\'F\'`` | Fixed point. Same as ``\'f\'``, but converts ``nan`` to |\n | | ``NAN`` and ``inf`` to ``INF``. |\n +-----------+------------------------------------------------------------+\n | ``\'g\'`` | General format. This prints the number as a fixed-point |\n | | number, unless the number is too large, in which case it |\n | | switches to ``\'e\'`` exponent notation. Infinity and NaN |\n | | values are formatted as ``inf``, ``-inf`` and ``nan``, |\n | | respectively. |\n +-----------+------------------------------------------------------------+\n | ``\'G\'`` | General format. Same as ``\'g\'`` except switches to ``\'E\'`` |\n | | if the number gets to large. The representations of |\n | | infinity and NaN are uppercased, too. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'g\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | ``\'%\'`` | Percentage. Multiplies the number by 100 and displays in |\n | | fixed (``\'f\'``) format, followed by a percent sign. |\n +-----------+------------------------------------------------------------+\n | None | Similar to ``\'g\'``, except with at least one digit past |\n | | the decimal point and a default precision of 12. This is |\n | | intended to match ``str()``, except you can add the other |\n | | format modifiers. |\n +-----------+------------------------------------------------------------+\n', 'function': '\nFunction definitions\n********************\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n', 'global': '\nThe ``global`` statement\n************************\n\n global_stmt ::= "global" identifier ("," identifier)*\n\nThe ``global`` statement is a declaration which holds for the entire\ncurrent code block. It means that the listed identifiers are to be\ninterpreted as globals. It would be impossible to assign to a global\nvariable without ``global``, although free variables may refer to\nglobals without being declared global.\n\nNames listed in a ``global`` statement must not be used in the same\ncode block textually preceding that ``global`` statement.\n\nNames listed in a ``global`` statement must not be defined as formal\nparameters or in a ``for`` loop control target, ``class`` definition,\nfunction definition, or ``import`` statement.\n\n(The current implementation does not enforce the latter two\nrestrictions, but programs should not abuse this freedom, as future\nimplementations may enforce them or silently change the meaning of the\nprogram.)\n\n**Programmer\'s note:** the ``global`` is a directive to the parser.\nIt applies only to code parsed at the same time as the ``global``\nstatement. In particular, a ``global`` statement contained in a string\nor code object supplied to the builtin ``exec()`` function does not\naffect the code block *containing* the function call, and code\ncontained in such a string is unaffected by ``global`` statements in\nthe code containing the function call. The same applies to the\n``eval()`` and ``compile()`` functions.\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 ::= id_start id_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\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\nAll identifiers are converted into the normal form NFC while parsing;\ncomparison of identifiers is based on NFC.\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);\n applications should not expect to define additional names using\n this convention. The set of names of this class defined by Python\n may be extended in future versions. See section *Special method\n names*.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n', 'if': '\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.\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.\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 for 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\nimprt mod`` from within ``pkg.subpkg1`` you will import\n``pkg.subpkg2.mod``. The specification for relative imports is\ncontained within **PEP 328**.\n\nThe built-in function ``__import__()`` is provided to support\napplications that determine which modules need to be loaded\ndynamically; refer to *Built-in Functions* for additional information.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python. The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language. It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n future_statement ::= "from" "__future__" "import" feature ["as" name]\n ("," feature ["as" name])*\n | "from" "__future__" "import" "(" feature ["as" name]\n ("," feature ["as" name])* [","] ")"\n feature ::= identifier\n name ::= identifier\n\nA future statement must appear near the top of the module. The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 3.0 are ``absolute_import``,\n``division``, ``generators``, ``unicode_literals``,\n``print_function``, ``nested_scopes`` and ``with_statement``. They\nare all redundant because they are always enabled, and only kept for\nbackwards compatibility.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code. It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently. Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by calls to the builtin functions ``exec()`` and\n``compile()`` that occur in a module ``M`` containing a future\nstatement will, by default, use the new syntax or semantics associated\nwith the future statement. This can be controlled by optional\narguments to ``compile()`` --- see the documentation of that function\nfor details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session. If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\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\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.\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.\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 for 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\nimprt 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 builtin functions ``exec()`` and\n``compile()`` that occur in a module ``M`` containing a future\nstatement will, by default, use the new syntax or semantics associated\nwith the future statement. This can be controlled by optional\narguments to ``compile()`` --- see the documentation of that function\nfor details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session. If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\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-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n are identical to themselves, ``x is x`` but are not equal to\n themselves, ``x != x``. Additionally, comparing any value to a\n not-a-number value will return ``False``. For example, both ``3 <\n float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``[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 their sorted\n ``(key, value)`` lists compare equal. [4] Outcomes other than\n equality are resolved consistently, but are not otherwise defined.\n [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, ``min()``, ``max()``, and ``sorted()`` produce\n undefined results given a list of sets as inputs.\n\n* Most other objects of builtin types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison. Most\nnumeric types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is. When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``. This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons. For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership. ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise. ``x\nnot in s`` returns the negation of ``x in s``. All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` is equivalent to ``any(x is e or x == e for val\ne in y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` and do\ndefine ``__getitem__()``, ``x in y`` is true if and only if there is a\nnon-negative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [6]\n', 'integers': '\nInteger literals\n****************\n\nInteger literals are described by the following lexical definitions:\n\n integer ::= decimalinteger | octinteger | hexinteger | bininteger\n decimalinteger ::= nonzerodigit digit* | "0"+\n nonzerodigit ::= "1"..."9"\n digit ::= "0"..."9"\n octinteger ::= "0" ("o" | "O") octdigit+\n hexinteger ::= "0" ("x" | "X") hexdigit+\n bininteger ::= "0" ("b" | "B") bindigit+\n octdigit ::= "0"..."7"\n hexdigit ::= digit | "a"..."f" | "A"..."F"\n bindigit ::= "0" | "1"\n\nThere is no limit for the length of integer literals apart from what\ncan be stored in available memory.\n\nNote that leading zeros in a non-zero decimal number are not allowed.\nThis is for disambiguation with C-style octal literals, which Python\nused before version 3.0.\n\nSome examples of integer literals:\n\n 7 2147483647 0o177 0b100110111\n 3 79228162514264337593543950336 0o377 0x100000000\n 79228162514264337593543950336 0xdeadbeef\n', 'lambda': '\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', @@ -50,7 +50,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss 'numbers': "\nNumeric literals\n****************\n\nThere are three types of numeric literals: integers, floating point\nnumbers, and imaginary numbers. There are no complex literals\n(complex numbers can be formed by adding a real number and an\nimaginary number).\n\nNote that numeric literals do not include a sign; a phrase like ``-1``\nis actually an expression composed of the unary operator '``-``' and\nthe literal ``1``.\n", 'numeric-types': "\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. [3] 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", 'objects': '\nObjects, values and types\n*************************\n\n*Objects* are Python\'s abstraction for data. All data in a Python\nprogram is represented by objects or by relations between objects. (In\na sense, and in conformance to Von Neumann\'s model of a "stored\nprogram computer," code is also represented by objects.)\n\nEvery object has an identity, a type and a value. An object\'s\n*identity* never changes once it has been created; you may think of it\nas the object\'s address in memory. The \'``is``\' operator compares the\nidentity of two objects; the ``id()`` function returns an integer\nrepresenting its identity (currently implemented as its address). An\nobject\'s *type* is also unchangeable. [1] An object\'s type determines\nthe operations that the object supports (e.g., "does it have a\nlength?") and also defines the possible values for objects of that\ntype. The ``type()`` function returns an object\'s type (which is an\nobject itself). The *value* of some objects can change. Objects\nwhose value can change are said to be *mutable*; objects whose value\nis unchangeable once they are created are called *immutable*. (The\nvalue of an immutable container object that contains a reference to a\nmutable object can change when the latter\'s value is changed; however\nthe container is still considered immutable, because the collection of\nobjects it contains cannot be changed. So, immutability is not\nstrictly the same as having an unchangeable value, it is more subtle.)\nAn object\'s mutability is determined by its type; for instance,\nnumbers, strings and tuples are immutable, while dictionaries and\nlists are mutable.\n\nObjects are never explicitly destroyed; however, when they become\nunreachable they may be garbage-collected. An implementation is\nallowed to postpone garbage collection or omit it altogether --- it is\na matter of implementation quality how garbage collection is\nimplemented, as long as no objects are collected that are still\nreachable. (Implementation note: CPython currently uses a reference-\ncounting scheme with (optional) delayed detection of cyclically linked\ngarbage, which collects most objects as soon as they become\nunreachable, but is not guaranteed to collect garbage containing\ncircular references. See the documentation of the ``gc`` module for\ninformation on controlling the collection of cyclic garbage. Other\nimplementations act differently and CPython may change.)\n\nNote that the use of the implementation\'s tracing or debugging\nfacilities may keep objects alive that would normally be collectable.\nAlso note that catching an exception with a \'``try``...``except``\'\nstatement may keep objects alive.\n\nSome objects contain references to "external" resources such as open\nfiles or windows. It is understood that these resources are freed\nwhen the object is garbage-collected, but since garbage collection is\nnot guaranteed to happen, such objects also provide an explicit way to\nrelease the external resource, usually a ``close()`` method. Programs\nare strongly recommended to explicitly close such objects. The\n\'``try``...``finally``\' statement and the \'``with``\' statement provide\nconvenient ways to do this.\n\nSome objects contain references to other objects; these are called\n*containers*. Examples of containers are tuples, lists and\ndictionaries. The references are part of a container\'s value. In\nmost cases, when we talk about the value of a container, we imply the\nvalues, not the identities of the contained objects; however, when we\ntalk about the mutability of a container, only the identities of the\nimmediately contained objects are implied. So, if an immutable\ncontainer (like a tuple) contains a reference to a mutable object, its\nvalue changes if that mutable object is changed.\n\nTypes affect almost all aspects of object behavior. Even the\nimportance of object identity is affected in some sense: for immutable\ntypes, operations that compute new values may actually return a\nreference to any existing object with the same type and value, while\nfor mutable objects this is not allowed. E.g., after ``a = 1; b =\n1``, ``a`` and ``b`` may or may not refer to the same object with the\nvalue one, depending on the implementation, but after ``c = []; d =\n[]``, ``c`` and ``d`` are guaranteed to refer to two different,\nunique, newly created empty lists. (Note that ``c = d = []`` assigns\nthe same object to both ``c`` and ``d``.)\n', - 'operator-summary': '\nSummary\n*******\n\nThe following table summarizes the operator precedences in Python,\nfrom lowest precedence (least binding) to highest precedence (most\nbinding). Operators in the same box have the same precedence. Unless\nthe syntax is explicitly given, operators are binary. Operators in\nthe same box group left to right (except for comparisons, including\ntests, which all have the same precedence and chain from left to right\n--- see section *Comparisons* --- and exponentiation, which groups\nfrom right to left).\n\n+-------------------------------------------------+---------------------------------------+\n| Operator | Description |\n+=================================================+=======================================+\n| ``lambda`` | Lambda expression |\n+-------------------------------------------------+---------------------------------------+\n| ``or`` | Boolean OR |\n+-------------------------------------------------+---------------------------------------+\n| ``and`` | Boolean AND |\n+-------------------------------------------------+---------------------------------------+\n| ``not`` *x* | Boolean NOT |\n+-------------------------------------------------+---------------------------------------+\n| ``in``, ``not`` ``in``, ``is``, ``is not``, | Comparisons, including membership |\n| ``<``, ``<=``, ``>``, ``>=``, ``<>``, ``!=``, | tests and identity tests, |\n| ``==`` | |\n+-------------------------------------------------+---------------------------------------+\n| ``|`` | Bitwise OR |\n+-------------------------------------------------+---------------------------------------+\n| ``^`` | Bitwise XOR |\n+-------------------------------------------------+---------------------------------------+\n| ``&`` | Bitwise AND |\n+-------------------------------------------------+---------------------------------------+\n| ``<<``, ``>>`` | Shifts |\n+-------------------------------------------------+---------------------------------------+\n| ``+``, ``-`` | Addition and subtraction |\n+-------------------------------------------------+---------------------------------------+\n| ``*``, ``/``, ``//``, ``%`` | Multiplication, division, remainder |\n+-------------------------------------------------+---------------------------------------+\n| ``+x``, ``-x``, ``~x`` | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| ``**`` | Exponentiation [7] |\n+-------------------------------------------------+---------------------------------------+\n| ``x[index]``, ``x[index:index]``, | Subscription, slicing, call, |\n| ``x(arguments...)``, ``x.attribute`` | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| ``(expressions...)``, ``[expressions...]``, | Binding or tuple display, list |\n| ``{key:datum...}``, | display, dictionary display, |\n+-------------------------------------------------+---------------------------------------+\n\n-[ Footnotes ]-\n\n[1] While ``abs(x%y) < abs(y)`` is true mathematically, for floats it\n may not be true numerically due to roundoff. For example, and\n assuming a platform on which a Python float is an IEEE 754 double-\n precision number, in order that ``-1e-100 % 1e100`` have the same\n sign as ``1e100``, the computed result is ``-1e-100 + 1e100``,\n which is numerically exactly equal to ``1e100``. Function\n ``fmod()`` in the ``math`` module returns a result whose sign\n matches the sign of the first argument instead, and so returns\n ``-1e-100`` in this case. Which approach is more appropriate\n depends on the application.\n\n[2] If x is very close to an exact integer multiple of y, it\'s\n possible for ``x//y`` to be one larger than ``(x-x%y)//y`` due to\n rounding. In such cases, Python returns the latter result, in\n order to preserve that ``divmod(x,y)[0] * y + x % y`` be very\n close to ``x``.\n\n[3] While comparisons between strings make sense at the byte level,\n they may be counter-intuitive to users. For example, the strings\n ``"\\u00C7"`` and ``"\\u0327\\u0043"`` compare differently, even\n though they both represent the same unicode character (LATIN\n CAPITAL LETTER C WITH CEDILLA). To compare strings in a human\n recognizable way, compare using ``unicodedata.normalize()``.\n\n[4] The implementation computes this efficiently, without constructing\n lists or sorting.\n\n[5] Earlier versions of Python used lexicographic comparison of the\n sorted (key, value) lists, but this was very expensive for the\n common case of comparing for equality. An even earlier version of\n Python compared dictionaries by identity only, but this caused\n surprises because people expected to be able to test a dictionary\n for emptiness by comparing it to ``{}``.\n\n[6] Due to automatic garbage-collection, free lists, and the dynamic\n nature of descriptors, you may notice seemingly unusual behaviour\n in certain uses of the ``is`` operator, like those involving\n comparisons between instance methods, or constants. Check their\n documentation for more info.\n\n[7] The power operator ``**`` binds less tightly than an arithmetic or\n bitwise unary operator on its right, that is, ``2**-1`` is\n ``0.5``.\n', + 'operator-summary': '\nSummary\n*******\n\nThe following table summarizes the operator precedences in Python,\nfrom lowest precedence (least binding) to highest precedence (most\nbinding). Operators in the same box have the same precedence. Unless\nthe syntax is explicitly given, operators are binary. Operators in\nthe same box group left to right (except for comparisons, including\ntests, which all have the same precedence and chain from left to right\n--- see section *Comparisons* --- and exponentiation, which groups\nfrom right to left).\n\n+-------------------------------------------------+---------------------------------------+\n| Operator | Description |\n+=================================================+=======================================+\n| ``lambda`` | Lambda expression |\n+-------------------------------------------------+---------------------------------------+\n| ``or`` | Boolean OR |\n+-------------------------------------------------+---------------------------------------+\n| ``and`` | Boolean AND |\n+-------------------------------------------------+---------------------------------------+\n| ``not`` *x* | Boolean NOT |\n+-------------------------------------------------+---------------------------------------+\n| ``in``, ``not`` ``in``, ``is``, ``is not``, | Comparisons, including membership |\n| ``<``, ``<=``, ``>``, ``>=``, ``!=``, ``==`` | tests and identity tests, |\n+-------------------------------------------------+---------------------------------------+\n| ``|`` | Bitwise OR |\n+-------------------------------------------------+---------------------------------------+\n| ``^`` | Bitwise XOR |\n+-------------------------------------------------+---------------------------------------+\n| ``&`` | Bitwise AND |\n+-------------------------------------------------+---------------------------------------+\n| ``<<``, ``>>`` | Shifts |\n+-------------------------------------------------+---------------------------------------+\n| ``+``, ``-`` | Addition and subtraction |\n+-------------------------------------------------+---------------------------------------+\n| ``*``, ``/``, ``//``, ``%`` | Multiplication, division, remainder |\n+-------------------------------------------------+---------------------------------------+\n| ``+x``, ``-x``, ``~x`` | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| ``**`` | Exponentiation [7] |\n+-------------------------------------------------+---------------------------------------+\n| ``x[index]``, ``x[index:index]``, | Subscription, slicing, call, |\n| ``x(arguments...)``, ``x.attribute`` | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| ``(expressions...)``, ``[expressions...]``, | Binding or tuple display, list |\n| ``{key:datum...}``, | display, dictionary display, |\n+-------------------------------------------------+---------------------------------------+\n\n-[ Footnotes ]-\n\n[1] While ``abs(x%y) < abs(y)`` is true mathematically, for floats it\n may not be true numerically due to roundoff. For example, and\n assuming a platform on which a Python float is an IEEE 754 double-\n precision number, in order that ``-1e-100 % 1e100`` have the same\n sign as ``1e100``, the computed result is ``-1e-100 + 1e100``,\n which is numerically exactly equal to ``1e100``. Function\n ``fmod()`` in the ``math`` module returns a result whose sign\n matches the sign of the first argument instead, and so returns\n ``-1e-100`` in this case. Which approach is more appropriate\n depends on the application.\n\n[2] If x is very close to an exact integer multiple of y, it\'s\n possible for ``x//y`` to be one larger than ``(x-x%y)//y`` due to\n rounding. In such cases, Python returns the latter result, in\n order to preserve that ``divmod(x,y)[0] * y + x % y`` be very\n close to ``x``.\n\n[3] While comparisons between strings make sense at the byte level,\n they may be counter-intuitive to users. For example, the strings\n ``"\\u00C7"`` and ``"\\u0327\\u0043"`` compare differently, even\n though they both represent the same unicode character (LATIN\n CAPITAL LETTER C WITH CEDILLA). To compare strings in a human\n recognizable way, compare using ``unicodedata.normalize()``.\n\n[4] The implementation computes this efficiently, without constructing\n lists or sorting.\n\n[5] Earlier versions of Python used lexicographic comparison of the\n sorted (key, value) lists, but this was very expensive for the\n common case of comparing for equality. An even earlier version of\n Python compared dictionaries by identity only, but this caused\n surprises because people expected to be able to test a dictionary\n for emptiness by comparing it to ``{}``.\n\n[6] Due to automatic garbage-collection, free lists, and the dynamic\n nature of descriptors, you may notice seemingly unusual behaviour\n in certain uses of the ``is`` operator, like those involving\n comparisons between instance methods, or constants. Check their\n documentation for more info.\n\n[7] The power operator ``**`` binds less tightly than an arithmetic or\n bitwise unary operator on its right, that is, ``2**-1`` is\n ``0.5``.\n', 'pass': '\nThe ``pass`` statement\n**********************\n\n pass_stmt ::= "pass"\n\n``pass`` is a null operation --- when it is executed, nothing happens.\nIt is useful as a placeholder when a statement is required\nsyntactically, but no code needs to be executed, for example:\n\n def f(arg): pass # a function that does nothing (yet)\n\n class C: pass # a class with no methods (yet)\n', 'power': '\nThe power operator\n******************\n\nThe power operator binds more tightly than unary operators on its\nleft; it binds less tightly than unary operators on its right. The\nsyntax is:\n\n power ::= primary ["**" u_expr]\n\nThus, in an unparenthesized sequence of power and unary operators, the\noperators are evaluated from right to left (this does not constrain\nthe evaluation order for the operands): ``-1**2`` results in ``-1``.\n\nThe power operator has the same semantics as the built-in ``pow()``\nfunction, when called with two arguments: it yields its left argument\nraised to the power of its right argument. The numeric arguments are\nfirst converted to a common type, and the result is of that type.\n\nFor int operands, the result has the same type as the operands unless\nthe second argument is negative; in that case, all arguments are\nconverted to float and a float result is delivered. For example,\n``10**2`` returns ``100``, but ``10**-2`` returns ``0.01``.\n\nRaising ``0.0`` to a negative power results in a\n``ZeroDivisionError``. Raising a negative number to a fractional power\nresults in a ``complex`` number. (In earlier versions it raised a\n``ValueError``.)\n', 'raise': '\nThe ``raise`` statement\n***********************\n\n raise_stmt ::= "raise" [expression ["from" expression]]\n\nIf no expressions are present, ``raise`` re-raises the last exception\nthat was active in the current scope. If no exception is active in\nthe current scope, a ``TypeError`` exception is raised indicating that\nthis is an error (if running under IDLE, a ``queue.Empty`` exception\nis raised instead).\n\nOtherwise, ``raise`` evaluates the first expression as the exception\nobject. It must be either a subclass or an instance of\n``BaseException``. If it is a class, the exception instance will be\nobtained when needed by instantiating the class with no arguments.\n\nThe *type* of the exception is the exception instance\'s class, the\n*value* is the instance itself.\n\nA traceback object is normally created automatically when an exception\nis raised and attached to it as the ``__traceback__`` attribute, which\nis writable. You can create an exception and set your own traceback in\none step using the ``with_traceback()`` exception method (which\nreturns the same exception instance, with its traceback set to its\nargument), like so:\n\n raise Exception("foo occurred").with_traceback(tracebackobj)\n\nThe ``from`` clause is used for exception chaining: if given, the\nsecond *expression* must be another exception class or instance, which\nwill then be attached to the raised exception as the ``__cause__``\nattribute (which is writable). If the raised exception is not\nhandled, both exceptions will be printed:\n\n >>> try:\n ... print(1 / 0)\n ... except Exception as exc:\n ... raise RuntimeError("Something bad happened") from exc\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n The above exception was the direct cause of the following exception:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nA similar mechanism works implicitly if an exception is raised inside\nan exception handler: the previous exception is then attached as the\nnew exception\'s ``__context__`` attribute:\n\n >>> try:\n ... print(1 / 0)\n ... except:\n ... raise RuntimeError("Something bad happened")\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n During handling of the above exception, another exception occurred:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information about handling exceptions is in section\n*The try statement*.\n', @@ -70,7 +70,7 @@ topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAss '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": 2, "two": 3}``:\n\n * ``dict(one=2, two=3)``\n\n * ``dict({\'one\': 2, \'two\': 3})``\n\n * ``dict(zip((\'one\', \'two\'), (2, 3)))``\n\n * ``dict([[\'two\', 3], [\'one\', 2]])``\n\n The first example only works for keys that are valid Python\n identifiers; the others work with any valid keys.\n\n 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. For an example, see ``collections.defaultdict``.\n\n d[key] = value\n\n Set ``d[key]`` to *value*.\n\n del d[key]\n\n Remove ``d[key]`` from *d*. Raises a ``KeyError`` if *key* is\n not in the map.\n\n key in d\n\n Return ``True`` if *d* has a key *key*, else ``False``.\n\n 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 ``iterkeys()``.\n\n clear()\n\n Remove all items from the dictionary.\n\n copy()\n\n Return a shallow copy of the dictionary.\n\n 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 below for documentation of view objects.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See below for\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 a tuple or other iterable of\n length two). If keyword arguments are specified, the\n dictionary is then is updated with those key/value pairs:\n ``d.update(red=1, blue=2)``.\n\n values()\n\n Return a new view of the dictionary\'s values. See below for\n documentation of view objects.\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 and\nhashable, then the items view is also set-like. (Values views are not\ntreated as set-like since the entries are generally not unique.) Then\nthese set operations are available ("other" refers either to another\nview or a set):\n\ndictview & other\n\n Return the intersection of the dictview and the other object as a\n new set.\n\ndictview | other\n\n Return the union of the dictview and the other object as a new set.\n\ndictview - other\n\n Return the difference between the dictview and the other object\n (all elements in *dictview* that aren\'t in *other*) as a new set.\n\ndictview ^ other\n\n Return the symmetric difference (all elements either in *dictview*\n or *other*, but not in both) of the dictview and the other object\n as a new set.\n\nAn example of dictionary view usage:\n\n >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n >>> keys = dishes.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', '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 member of every module is ``__dict__``. This is the\ndictionary containing the module's symbol table. Modifying this\ndictionary will actually change the module's symbol table, but direct\nassignment to the ``__dict__`` attribute is not possible (you can\nwrite ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but\nyou can't write ``m.__dict__ = {}``). Modifying ``__dict__`` directly\nis not recommended.\n\nModules built into the interpreter are written like this: ``<module\n'sys' (built-in)>``. If loaded from a file, they are written as\n``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.\n", - 'typesseq': '\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\nbe constructed the constructor, ``bytes()``, and from literals; use a\n``b`` prefix with normal string syntax: ``b\'xyzzy\'``. To construct\nbyte arrays, use the ``bytearray()`` function.\n\nWarning: While string objects are sequences of characters (represented by\n strings of length 1), bytes and bytearray objects are sequences of\n *integers* (between 0 and 255), representing the ASCII value of\n single bytes. That means that for a bytes or bytearray object *b*,\n ``b[0]`` will be an integer, while ``b[0:1]`` will be a bytes or\n bytearray object of length 1. The representation of bytes objects\n uses the literal format (``b\'...\'``) since it is generally more\n useful than e.g. ``bytes([50, 19, 100])``. You can always convert a\n bytes object into a list of integers using ``list(b)``.Also, while\n in previous Python versions, byte strings and Unicode strings could\n be exchanged for each other rather freely (barring encoding issues),\n strings and bytes are now completely separate concepts. There\'s no\n implicit en-/decoding if you pass and object of the wrong type. A\n string always compares unequal to a bytes or bytearray 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 slicing, concatenation or repetition, and using\n``in``, ``not in``, ``min()`` or ``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* and *j* are\nintegers:\n\n+--------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+====================+==================================+============+\n| ``x in s`` | ``True`` if an item of *s* is | (1) |\n| | equal to *x*, else ``False`` | |\n+--------------------+----------------------------------+------------+\n| ``x not in s`` | ``False`` if an item of *s* is | (1) |\n| | equal to *x*, else ``True`` | |\n+--------------------+----------------------------------+------------+\n| ``s + t`` | the concatenation of *s* and *t* | (6) |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s`` | *n* shallow copies of *s* | (2) |\n| | concatenated | |\n+--------------------+----------------------------------+------------+\n| ``s[i]`` | *i*\'th item of *s*, origin 0 | (3) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]`` | slice of *s* from *i* to *j* | (3)(4) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]`` | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+--------------------+----------------------------------+------------+\n| ``len(s)`` | length of *s* | |\n+--------------------+----------------------------------+------------+\n| ``min(s)`` | smallest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``max(s)`` | largest item of *s* | |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular, tuples and\nlists are compared lexicographically by comparing corresponding\nelements. This means that to compare equal, every element must\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. If *s* and *t* are both strings, some Python implementations such\n as CPython can usually perform an in-place optimization for\n assignments of the form ``s=s+t`` or ``s+=t``. When applicable,\n this optimization makes quadratic run-time much less likely. This\n optimization is both version and implementation dependent. For\n performance sensitive code, it is preferable to use the\n ``str.join()`` method which assures consistent linear concatenation\n performance across versions and implementations.\n\n\nString Methods\n==============\n\nString objects support the methods listed below. Note that none of\nthese methods take keyword arguments.\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 only its first character\n capitalized.\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[, errors]])\n\n Return an encoded version of the string as a bytes object. Default\n encoding is the current default string encoding. *errors* may be\n given to set a different error handling scheme. The default for\n *errors* is ``\'strict\'``, meaning that encoding errors raise a\n ``UnicodeError``. Other possible values are ``\'ignore\'``,\n ``\'replace\'``, ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and\n any other name registered via ``codecs.register_error()``, see\n section *Codec Base Classes*. For a list of possible encodings, see\n section *Standard Encodings*.\n\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 one or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the range [*start*, *end*].\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\nstr.format(*args, **kwargs)\n\n Perform a string formatting operation. The *format_string*\n argument can contain literal text or replacement fields delimited\n by braces ``{}``. Each replacement field contains either the\n numeric index of a positional argument, or the name of a keyword\n argument. Returns a copy of *format_string* where each replacement\n field is replaced with the string value of the corresponding\n argument.\n\n >>> "The sum of 1 + 2 is {0}".format(1+2)\n \'The sum of 1 + 2 is 3\'\n\n See *Format String Syntax* for a description of the various\n formatting options that can be specified in format strings.\n\nstr.index(sub[, start[, end]])\n\n Like ``find()``, but raise ``ValueError`` when the substring is not\n found.\n\nstr.isalnum()\n\n Return true if all characters in the string are alphanumeric and\n there is at least one character, false otherwise.\n\nstr.isalpha()\n\n Return true if all characters in the string are alphabetic and\n there is at least one character, false otherwise.\n\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 include digit characters, and all characters that that\n can be used to form decimal-radix numbers, e.g. U+0660, ARABIC-\n 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.\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 in the string are lowercase and\n 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.\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.\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 in the string are uppercase and\n there is at least one cased character, false otherwise.\n\nstr.join(seq)\n\n Return a string which is the concatenation of the strings in the\n sequence *seq*. A ``TypeError`` will be raised if there are any\n non-string values in *seq*, including ``bytes`` objects. The\n 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\n ``len(s)``.\n\nstr.lower()\n\n Return a copy of the string converted to lowercase.\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]. Optional\n arguments *start* and *end* are interpreted as in slice notation.\n Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n is not found.\n\nstr.rjust(width[, fillchar])\n\n Return the string right justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than\n ``len(s)``.\n\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[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n are done, the *rightmost* ones. If *sep* is not specified or\n ``None``, any whitespace string is a separator. Except for\n splitting from the right, ``rsplit()`` behaves like ``split()``\n which is described in detail below.\n\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[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit*\n splits are done (thus, the list will have at most ``maxsplit+1``\n elements). If *maxsplit* is not specified, then there is no limit\n on the number of splits (all possible splits are made).\n\n If *sep* is given, consecutive delimiters are not grouped together\n and are deemed to delimit empty strings (for example,\n ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``). The *sep*\n argument may consist of multiple characters (for example,\n ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n an empty string with a specified separator returns ``[\'\']``.\n\n If *sep* is not specified or is ``None``, a different splitting\n algorithm is applied: runs of consecutive whitespace are regarded\n as a single separator, and the result will contain no empty strings\n at the start or end if the string has leading or trailing\n whitespace. Consequently, splitting an empty string or a string\n consisting of just whitespace with a ``None`` separator returns\n ``[]``.\n\n For example, ``\' 1 2 3 \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n and ``\' 1 2 3 \'.split(None, 1)`` returns ``[\'1\', \'2 3 \']``.\n\nstr.splitlines([keepends])\n\n Return a list of the lines in the string, breaking at line\n boundaries. Line breaks are not included in the resulting list\n unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n Return ``True`` if string starts with the *prefix*, otherwise\n return ``False``. *prefix* can also be a tuple of prefixes to look\n for. With optional *start*, test string beginning at that\n position. With optional *end*, stop comparing string at that\n position.\n\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.\n\nstr.title()\n\n Return a titlecased version of the string: words start with\n uppercase characters, all remaining cased characters are lowercase.\n\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 converted to uppercase.\n\nstr.zfill(width)\n\n Return the numeric string left filled with zeros in a string of\n length *width*. A sign prefix is handled correctly. The original\n string is returned if *width* is less than ``len(s)``.\n\n\nOld String Formatting Operations\n================================\n\nNote: The formatting operations described here are obsolete and may go\n away in future versions of Python. Use the new *String Formatting*\n in new code.\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. [4] Otherwise, *values* must be a tuple with exactly\nthe number of items specified by the format string, or a single\nmapping object (for example, a dictionary).\n\nA conversion specifier contains two or more characters and has the\nfollowing components, which must occur in this order:\n\n1. The ``\'%\'`` character, which marks the start of the specifier.\n\n2. Mapping key (optional), consisting of a parenthesised sequence of\n characters (for example, ``(somename)``).\n\n3. Conversion flags (optional), which affect the result of some\n conversion types.\n\n4. Minimum field width (optional). If specified as an ``\'*\'``\n (asterisk), the actual width is read from the next element of the\n tuple in *values*, and the object to convert comes after the\n minimum field width and optional precision.\n\n5. Precision (optional), given as a ``\'.\'`` (dot) followed by the\n precision. If specified as ``\'*\'`` (an asterisk), the actual width\n is read from the next element of the tuple in *values*, and the\n value to convert comes after the precision.\n\n6. Length modifier (optional).\n\n7. Conversion type.\n\nWhen the right argument is a dictionary (or other mapping type), then\nthe formats in the string *must* include a parenthesised mapping key\ninto that dictionary inserted immediately after the ``\'%\'`` character.\nThe mapping key selects the value to be formatted from the mapping.\nFor example:\n\n>>> print(\'%(language)s has %(#)03d quote types.\' % \\\n... {\'language\': "Python", "#": 2})\nPython has 002 quote types.\n\nIn this case no ``*`` specifiers may occur in a format (since they\nrequire a sequential parameter list).\n\nThe conversion flag characters are:\n\n+-----------+-----------------------------------------------------------------------+\n| Flag | Meaning |\n+===========+=======================================================================+\n| ``\'#\'`` | The value conversion will use the "alternate form" (where defined |\n| | below). |\n+-----------+-----------------------------------------------------------------------+\n| ``\'0\'`` | The conversion will be zero padded for numeric values. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'-\'`` | The converted value is left adjusted (overrides the ``\'0\'`` |\n| | conversion if both are given). |\n+-----------+-----------------------------------------------------------------------+\n| ``\' \'`` | (a space) A blank should be left before a positive number (or empty |\n| | string) produced by a signed conversion. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'+\'`` | A sign character (``\'+\'`` or ``\'-\'``) will precede the conversion |\n| | (overrides a "space" flag). |\n+-----------+-----------------------------------------------------------------------+\n\nA length modifier (``h``, ``l``, or ``L``) may be present, but is\nignored as it is not necessary for Python -- so e.g. ``%ld`` is\nidentical to ``%d``.\n\nThe conversion types are:\n\n+--------------+-------------------------------------------------------+---------+\n| Conversion | Meaning | Notes |\n+==============+=======================================================+=========+\n| ``\'d\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'i\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'o\'`` | Signed octal value. | (1) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'u\'`` | 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()``). | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'%\'`` | No argument is converted, results in a ``\'%\'`` | |\n| | character in the result. | |\n+--------------+-------------------------------------------------------+---------+\n\nNotes:\n\n1. The alternate form causes a leading zero (``\'0\'``) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n2. The alternate form causes a leading ``\'0x\'`` or ``\'0X\'`` (depending\n on whether the ``\'x\'`` or ``\'X\'`` format was used) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n3. The alternate form causes the result to always contain a decimal\n point, even if no digits follow it.\n\n The precision determines the number of digits after the decimal\n point and defaults to 6.\n\n4. The alternate form causes the result to always contain a decimal\n point, and trailing zeroes are not removed as they would otherwise\n be.\n\n The precision determines the number of significant digits before\n and after the decimal point and defaults to 6.\n\n5. The precision determines the maximal number of characters used.\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. There are no consistent performance\nadvantages.\n\nRange objects have very little behavior: they only support indexing,\niteration, and the ``len()`` function.\n\n\nMutable Sequence Types\n======================\n\nList and bytearray objects support additional operations that 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.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``.\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 While a list is being sorted, the effect of attempting to mutate,\n or even inspect, the list is undefined. The C implementation makes\n the list appear empty for the duration, and raises ``ValueError``\n if it can detect that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\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\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[, errors]])\nbytearray.decode([encoding[, errors]])\n\n Return a string decoded from the given bytes. Default encoding is\n the current default string encoding. *errors* may be given to set\n a different error handling scheme. The default for *errors* is\n ``\'strict\'``, meaning that encoding errors raise a\n ``UnicodeError``. Other possible values are ``\'ignore\'``,\n ``\'replace\'`` and any other name registered via\n ``codecs.register_error()``, see section *Codec Base Classes*. For\n a list of possible encodings, see section *Standard Encodings*.\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])\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)\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\nbe constructed the constructor, ``bytes()``, and from literals; use a\n``b`` prefix with normal string syntax: ``b\'xyzzy\'``. To construct\nbyte arrays, use the ``bytearray()`` function.\n\nWarning: While string objects are sequences of characters (represented by\n strings of length 1), bytes and bytearray objects are sequences of\n *integers* (between 0 and 255), representing the ASCII value of\n single bytes. That means that for a bytes or bytearray object *b*,\n ``b[0]`` will be an integer, while ``b[0:1]`` will be a bytes or\n bytearray object of length 1. The representation of bytes objects\n uses the literal format (``b\'...\'``) since it is generally more\n useful than e.g. ``bytes([50, 19, 100])``. You can always convert a\n bytes object into a list of integers using ``list(b)``.Also, while\n in previous Python versions, byte strings and Unicode strings could\n be exchanged for each other rather freely (barring encoding issues),\n strings and bytes are now completely separate concepts. There\'s no\n implicit en-/decoding if you pass and object of the wrong type. A\n string always compares unequal to a bytes or bytearray 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 slicing, concatenation or repetition, and using\n``in``, ``not in``, ``min()`` or ``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* and *j* are\nintegers:\n\n+--------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+====================+==================================+============+\n| ``x in s`` | ``True`` if an item of *s* is | (1) |\n| | equal to *x*, else ``False`` | |\n+--------------------+----------------------------------+------------+\n| ``x not in s`` | ``False`` if an item of *s* is | (1) |\n| | equal to *x*, else ``True`` | |\n+--------------------+----------------------------------+------------+\n| ``s + t`` | the concatenation of *s* and *t* | (6) |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s`` | *n* shallow copies of *s* | (2) |\n| | concatenated | |\n+--------------------+----------------------------------+------------+\n| ``s[i]`` | *i*\'th item of *s*, origin 0 | (3) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]`` | slice of *s* from *i* to *j* | (3)(4) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]`` | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+--------------------+----------------------------------+------------+\n| ``len(s)`` | length of *s* | |\n+--------------------+----------------------------------+------------+\n| ``min(s)`` | smallest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``max(s)`` | largest item of *s* | |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular, tuples and\nlists are compared lexicographically by comparing corresponding\nelements. This means that to compare equal, every element must\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. If *s* and *t* are both strings, some Python implementations such\n as CPython can usually perform an in-place optimization for\n assignments of the form ``s=s+t`` or ``s+=t``. When applicable,\n this optimization makes quadratic run-time much less likely. This\n optimization is both version and implementation dependent. For\n performance sensitive code, it is preferable to use the\n ``str.join()`` method which assures consistent linear concatenation\n performance across versions and implementations.\n\n\nString Methods\n==============\n\nString objects support the methods listed below. Note that none of\nthese methods take keyword arguments.\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 only its first character\n capitalized.\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[, errors]])\n\n Return an encoded version of the string as a bytes object. Default\n encoding is the current default string encoding. *errors* may be\n given to set a different error handling scheme. The default for\n *errors* is ``\'strict\'``, meaning that encoding errors raise a\n ``UnicodeError``. Other possible values are ``\'ignore\'``,\n ``\'replace\'``, ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and\n any other name registered via ``codecs.register_error()``, see\n section *Codec Base Classes*. For a list of possible encodings, see\n section *Standard Encodings*.\n\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 one or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the range [*start*, *end*].\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\nstr.format(*args, **kwargs)\n\n Perform a string formatting operation. The *format_string*\n argument can contain literal text or replacement fields delimited\n by braces ``{}``. Each replacement field contains either the\n numeric index of a positional argument, or the name of a keyword\n argument. Returns a copy of *format_string* where each replacement\n field is replaced with the string value of the corresponding\n argument.\n\n >>> "The sum of 1 + 2 is {0}".format(1+2)\n \'The sum of 1 + 2 is 3\'\n\n See *Format String Syntax* for a description of the various\n formatting options that can be specified in format strings.\n\nstr.index(sub[, start[, end]])\n\n Like ``find()``, but raise ``ValueError`` when the substring is not\n found.\n\nstr.isalnum()\n\n Return true if all characters in the string are alphanumeric and\n there is at least one character, false otherwise.\n\nstr.isalpha()\n\n Return true if all characters in the string are alphabetic and\n there is at least one character, false otherwise.\n\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 include digit characters, and all characters that that\n can be used to form decimal-radix numbers, e.g. U+0660, ARABIC-\n 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.\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 in the string are lowercase and\n 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.\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.\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 in the string are uppercase and\n there is at least one cased character, false otherwise.\n\nstr.join(seq)\n\n Return a string which is the concatenation of the strings in the\n sequence *seq*. A ``TypeError`` will be raised if there are any\n non-string values in *seq*, including ``bytes`` objects. The\n 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\n ``len(s)``.\n\nstr.lower()\n\n Return a copy of the string converted to lowercase.\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]. Optional\n arguments *start* and *end* are interpreted as in slice notation.\n Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n is not found.\n\nstr.rjust(width[, fillchar])\n\n Return the string right justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than\n ``len(s)``.\n\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[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n are done, the *rightmost* ones. If *sep* is not specified or\n ``None``, any whitespace string is a separator. Except for\n splitting from the right, ``rsplit()`` behaves like ``split()``\n which is described in detail below.\n\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[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit*\n splits are done (thus, the list will have at most ``maxsplit+1``\n elements). If *maxsplit* is not specified, then there is no limit\n on the number of splits (all possible splits are made).\n\n If *sep* is given, consecutive delimiters are not grouped together\n and are deemed to delimit empty strings (for example,\n ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``). The *sep*\n argument may consist of multiple characters (for example,\n ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n an empty string with a specified separator returns ``[\'\']``.\n\n If *sep* is not specified or is ``None``, a different splitting\n algorithm is applied: runs of consecutive whitespace are regarded\n as a single separator, and the result will contain no empty strings\n at the start or end if the string has leading or trailing\n whitespace. Consequently, splitting an empty string or a string\n consisting of just whitespace with a ``None`` separator returns\n ``[]``.\n\n For example, ``\' 1 2 3 \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n and ``\' 1 2 3 \'.split(None, 1)`` returns ``[\'1\', \'2 3 \']``.\n\nstr.splitlines([keepends])\n\n Return a list of the lines in the string, breaking at line\n boundaries. Line breaks are not included in the resulting list\n unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n Return ``True`` if string starts with the *prefix*, otherwise\n return ``False``. *prefix* can also be a tuple of prefixes to look\n for. With optional *start*, test string beginning at that\n position. With optional *end*, stop comparing string at that\n position.\n\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.\n\nstr.title()\n\n Return a titlecased version of the string: words start with\n uppercase characters, all remaining cased characters are lowercase.\n\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 converted to uppercase.\n\nstr.zfill(width)\n\n Return the numeric string left filled with zeros in a string of\n length *width*. A sign prefix is handled correctly. The original\n string is returned if *width* is less than ``len(s)``.\n\n\nOld String Formatting Operations\n================================\n\nNote: The formatting operations described here are obsolete and may go\n away in future versions of Python. Use the new *String Formatting*\n in new code.\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. [4] Otherwise, *values* must be a tuple with exactly\nthe number of items specified by the format string, or a single\nmapping object (for example, a dictionary).\n\nA conversion specifier contains two or more characters and has the\nfollowing components, which must occur in this order:\n\n1. The ``\'%\'`` character, which marks the start of the specifier.\n\n2. Mapping key (optional), consisting of a parenthesised sequence of\n characters (for example, ``(somename)``).\n\n3. Conversion flags (optional), which affect the result of some\n conversion types.\n\n4. Minimum field width (optional). If specified as an ``\'*\'``\n (asterisk), the actual width is read from the next element of the\n tuple in *values*, and the object to convert comes after the\n minimum field width and optional precision.\n\n5. Precision (optional), given as a ``\'.\'`` (dot) followed by the\n precision. If specified as ``\'*\'`` (an asterisk), the actual width\n is read from the next element of the tuple in *values*, and the\n value to convert comes after the precision.\n\n6. Length modifier (optional).\n\n7. Conversion type.\n\nWhen the right argument is a dictionary (or other mapping type), then\nthe formats in the string *must* include a parenthesised mapping key\ninto that dictionary inserted immediately after the ``\'%\'`` character.\nThe mapping key selects the value to be formatted from the mapping.\nFor example:\n\n>>> print(\'%(language)s has %(#)03d quote types.\' % \\\n... {\'language\': "Python", "#": 2})\nPython has 002 quote types.\n\nIn this case no ``*`` specifiers may occur in a format (since they\nrequire a sequential parameter list).\n\nThe conversion flag characters are:\n\n+-----------+-----------------------------------------------------------------------+\n| Flag | Meaning |\n+===========+=======================================================================+\n| ``\'#\'`` | The value conversion will use the "alternate form" (where defined |\n| | below). |\n+-----------+-----------------------------------------------------------------------+\n| ``\'0\'`` | The conversion will be zero padded for numeric values. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'-\'`` | The converted value is left adjusted (overrides the ``\'0\'`` |\n| | conversion if both are given). |\n+-----------+-----------------------------------------------------------------------+\n| ``\' \'`` | (a space) A blank should be left before a positive number (or empty |\n| | string) produced by a signed conversion. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'+\'`` | A sign character (``\'+\'`` or ``\'-\'``) will precede the conversion |\n| | (overrides a "space" flag). |\n+-----------+-----------------------------------------------------------------------+\n\nA length modifier (``h``, ``l``, or ``L``) may be present, but is\nignored as it is not necessary for Python -- so e.g. ``%ld`` is\nidentical to ``%d``.\n\nThe conversion types are:\n\n+--------------+-------------------------------------------------------+---------+\n| Conversion | Meaning | Notes |\n+==============+=======================================================+=========+\n| ``\'d\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'i\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'o\'`` | Signed octal value. | (1) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'u\'`` | 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()``). | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'%\'`` | No argument is converted, results in a ``\'%\'`` | |\n| | character in the result. | |\n+--------------+-------------------------------------------------------+---------+\n\nNotes:\n\n1. The alternate form causes a leading zero (``\'0\'``) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n2. The alternate form causes a leading ``\'0x\'`` or ``\'0X\'`` (depending\n on whether the ``\'x\'`` or ``\'X\'`` format was used) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n3. The alternate form causes the result to always contain a decimal\n point, even if no digits follow it.\n\n The precision determines the number of digits after the decimal\n point and defaults to 6.\n\n4. The alternate form causes the result to always contain a decimal\n point, and trailing zeroes are not removed as they would otherwise\n be.\n\n The precision determines the number of significant digits before\n and after the decimal point and defaults to 6.\n\n5. The precision determines the maximal number of characters used.\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. There are no consistent performance\nadvantages.\n\nRange objects have very little behavior: they only support indexing,\niteration, and the ``len()`` function.\n\n\nMutable Sequence Types\n======================\n\nList and bytearray objects support additional operations that 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.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``.\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 While a list is being sorted, the effect of attempting to mutate,\n or even inspect, the list is undefined. The C implementation makes\n the list appear empty for the duration, and raises ``ValueError``\n if it can detect that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\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\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[, errors]])\nbytearray.decode([encoding[, errors]])\n\n Return a string decoded from the given bytes. Default encoding is\n the current default string encoding. *errors* may be given to set\n a different error handling scheme. The default for *errors* is\n ``\'strict\'``, meaning that encoding errors raise a\n ``UnicodeError``. Other possible values are ``\'ignore\'``,\n ``\'replace\'`` and any other name registered via\n ``codecs.register_error()``, see section *Codec Base Classes*. For\n a list of possible encodings, see section *Standard Encodings*.\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.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``.\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 While a list is being sorted, the effect of attempting to mutate,\n or even inspect, the list is undefined. The C implementation makes\n the list appear empty for the duration, and raises ``ValueError``\n if it can detect that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\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', |