topics={'assert':u'\nThe ``assert`` statement\n************************\n\nAssert statements are a convenient way to insert debugging assertions\ninto a program:\n\n assert_stmt ::= "assert" expression ["," expression]\n\nThe simple form, ``assert expression``, is equivalent to\n\n if __debug__:\n if not expression: raise AssertionError\n\nThe extended form, ``assert expression1, expression2``, is equivalent\nto\n\n if __debug__:\n if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that ``__debug__`` and ``AssertionError``\nrefer to the built-in variables with those names. In the current\nimplementation, the built-in variable ``__debug__`` is ``True`` under\nnormal circumstances, ``False`` when optimization is requested\n(command line option -O). The current code generator emits no code\nfor an assert statement when optimization is requested at compile\ntime. Note that it is unnecessary to include the source code for the\nexpression that failed in the error message; it will be displayed as\npart of the stack trace.\n\nAssignments to ``__debug__`` are illegal. The value for the built-in\nvariable is determined when the interpreter starts.\n',
'assignment':u'\nAssignment statements\n*********************\n\nAssignment statements are used to (re)bind names to values and to\nmodify attributes or items of mutable objects:\n\n assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)\n target_list ::= target ("," target)* [","]\n target ::= identifier\n | "(" target_list ")"\n | "[" target_list "]"\n | attributeref\n | subscription\n | slicing\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable. The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list is recursively defined as\nfollows.\n\n* If the target list is a single target: The object is assigned to\n that target.\n\n* If the target list is a comma-separated list of targets: The object\n must be 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\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n * If the name does not occur in a ``global`` statement in the\n current code block: the name is bound to the object in the current\n local namespace.\n\n * Otherwise: the name is bound to the object in the current global\n namespace.\n\n The name is rebound if it was already bound. This may cause the\n reference count for the object previously bound to the name to reach\n zero, causing the object to be deallocated and its destructor (if it\n has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in square\n brackets: The object must be an iterable with the same number of\n items as there are targets in the target list, and its items are\n assigned, from left to right, to the corresponding targets.\n\n* If the target is an attribute reference: The primary expression in\n the reference is evaluated. It should yield an object with\n assignable attributes; if this is not the case, ``TypeError`` is\n raised. That object is then asked to assign the assigned object to\n the given attribute; if it cannot perform the assignment, it raises\n an exception (usually but not necessarily ``AttributeError``).\n\n Note: If the object is a class instance and the attribute reference\n occurs on both sides of the assignment operator, the RHS expression,\n ``a.x`` can access either an instance attribute or (if no instance\n attribute exists) a class attribute. The LHS target ``a.x`` is\n always set as an instance attribute, creating it if necessary.\n Thus, the two occurrences of ``a.x`` do not necessarily refer to the\n same attribute: if the RHS expression refers to a class attribute,\n the LHS creates a new instance attribute as the target of the\n assignment:\n\n class Cls:\n x = 3 # class variable\n inst = Cls()\n inst.x = inst.x + 1 # writes inst.x as 4 leaving Cls.x as 3\n\n This description does not necessarily apply to descriptor\n attributes, such as properties creat
'atom-identifiers':u'\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name. See section\n*Identifiers and keywords* for lexical definition and section *Naming\nand binding* for documentation of naming and binding.\n\nWhen the name is bound to an object, evaluation of the atom yields\nthat object. When a name is not bound, an attempt to evaluate it\nraises a ``NameError`` exception.\n\n**Private name mangling:** When an identifier that textually occurs in\na class definition begins with two or more underscore characters and\ndoes not end in two or more underscores, it is considered a *private\nname* of that class. Private names are transformed to a longer form\nbefore code is generated for them. The transformation inserts the\nclass name in front of the name, with leading underscores removed, and\na single underscore inserted in front of the class name. For example,\nthe identifier ``__spam`` occurring in a class named ``Ham`` will be\ntransformed to ``_Ham__spam``. This transformation is independent of\nthe syntactical context in which the identifier is used. If the\ntransformed name is extremely long (longer than 255 characters),\nimplementation defined truncation may happen. If the class name\nconsists only of underscores, no transformation is done.\n',
'atom-literals':u"\nLiterals\n********\n\nPython supports string literals and various numeric literals:\n\n literal ::= stringliteral | integer | longinteger\n | floatnumber | imagnumber\n\nEvaluation of a literal yields an object of the given type (string,\ninteger, long integer, floating point number, complex number) with the\ngiven value. The value may be approximated in the case of floating\npoint and imaginary (complex) literals. See section *Literals* for\ndetails.\n\nAll literals correspond to immutable data types, and hence the\nobject's identity is less important than its value. Multiple\nevaluations of literals with the same value (either the same\noccurrence in the program text or a different occurrence) may obtain\nthe same object or a different object with the same value.\n",
'attribute-access':u'\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control in new-style classes.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should not simply execute ``self.name = value`` --- this would\n cause a recursive call to itself. Instead, it should insert the\n value in the dictionary of instance attributes, e.g.,\n ``self.__dict__[name] = value``. For new-style classes, rather\n than accessing the instance dictionary, it should call the base\n class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignment. This should only be implemented if ``del obj.name`` is\n meaningful for the object.\n\n\nMore attribute access for new-style classes\n===========================================\n\nThe following methods only apply to new-style classes.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines\n ``__getattr__()``, the latter will not be called unless\n ``__getattribute__()`` either calls it explicitly or raises an\n ``AttributeError``. This method should return the (computed)\n attribute value or raise an ``AttributeError`` exception. In order\n to avoid infinite recursion in this method, its implementation\n should always call the base class method with the same name to\n access any attributes it needs, for example,\n ``object.__getattribute__(self, name)``.\n\n Note: This method may still be bypassed when looking up special methods\n as the result of implicit invocation via language syntax or\n built-in functions. See *Special method lookup for new-style\n classes*.\n\n\nImplementing Descriptors\n========================\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in the\nclass dictionary of another new-style class, known as the *owner*\nclass. In the examples below, "the attribute" refers to the attribute\nwhose name is the key of the property in the owner class\'\n``__dict__``. Descriptors can only be implemented as new-style\nclasses themselves.\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or ``None`` when\n the attribute is accessed
'attribute-references':u'\nAttribute references\n********************\n\nAn attribute reference is a primary followed by a period and a name:\n\n attributeref ::= primary "." identifier\n\nThe primary must evaluate to an object of a type that supports\nattribute references, e.g., a module, list, or an instance. This\nobject is then asked to produce the attribute whose name is the\nidentifier. If this attribute is not available, the exception\n``AttributeError`` is raised. Otherwise, the type and value of the\nobject produced is determined by the object. Multiple evaluations of\nthe same attribute reference may yield different objects.\n',
'augassign':u'\nAugmented assignment statements\n*******************************\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n augtarget ::= identifier | attributeref | subscription | slicing\n augop ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like ``x += 1`` can be rewritten as\n``x = x + 1`` to achieve a similar, but not exactly equal effect. In\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',
'binary':u'\nBinary arithmetic operations\n****************************\n\nThe binary arithmetic operations have the conventional priority\nlevels. Note that some of these operations also apply to certain non-\nnumeric types. Apart from the power operator, there are only two\nlevels, one for multiplicative operators and one for additive\noperators:\n\n m_expr ::= u_expr | m_expr "*" u_expr | m_expr "//" u_expr | m_expr "/" u_expr\n | m_expr "%" u_expr\n a_expr ::= m_expr | a_expr "+" m_expr | a_expr "-" m_expr\n\nThe ``*`` (multiplication) operator yields the product of its\narguments. The arguments must either both be numbers, or one argument\nmust be an integer (plain or long) and the other must be a sequence.\nIn the former case, the numbers are converted to a common type and\nthen multiplied together. In the latter case, sequence repetition is\nperformed; a negative repetition factor yields an empty sequence.\n\nThe ``/`` (division) and ``//`` (floor division) operators yield the\nquotient of their arguments. The numeric arguments are first\nconverted to a common type. Plain or long integer division yields an\ninteger of the same type; the result is that of mathematical division\nwith the \'floor\' function applied to the result. Division by zero\nraises the ``ZeroDivisionError`` exception.\n\nThe ``%`` (modulo) operator yields the remainder from the division of\nthe first argument by the second. The numeric arguments are first\nconverted to a common type. A zero right argument raises the\n``ZeroDivisionError`` exception. The arguments may be floating point\nnumbers, e.g., ``3.14%0.7`` equals ``0.34`` (since ``3.14`` equals\n``4*0.7 + 0.34``.) The modulo operator always yields a result with\nthe same sign as its second operand (or zero); the absolute value of\nthe result is strictly smaller than the absolute value of the second\noperand [2].\n\nThe integer division and modulo operators are connected by the\nfollowing identity: ``x == (x/y)*y + (x%y)``. Integer division and\nmodulo are also connected with the built-in function ``divmod()``:\n``divmod(x, y) == (x/y, x%y)``. These identities don\'t hold for\nfloating point numbers; there similar identities hold approximately\nwhere ``x/y`` is replaced by ``floor(x/y)`` or ``floor(x/y) - 1`` [3].\n\nIn addition to performing the modulo operation on numbers, the ``%``\noperator is also overloaded by string and unicode objects to perform\nstring formatting (also known as interpolation). The syntax for string\nformatting is described in the Python Library Reference, section\n*String Formatting Operations*.\n\nDeprecated since version 2.3: The floor division operator, the modulo\noperator, and the ``divmod()`` function are no longer defined for\ncomplex numbers. Instead, convert to a floating point number using\nthe ``abs()`` function if appropriate.\n\nThe ``+`` (addition) operator yields the sum of its arguments. The\narguments must either both be numbers or both sequences of the same\ntype. In the former case, the numbers are converted to a common type\nand then added together. In the latter case, the sequences are\nconcatenated.\n\nThe ``-`` (subtraction) operator yields the difference of its\narguments. The numeric arguments are first converted to a common\ntype.\n',
'bitwise':u'\nBinary bitwise operations\n*************************\n\nEach of the three bitwise operations has a different priority level:\n\n and_expr ::= shift_expr | and_expr "&" shift_expr\n xor_expr ::= and_expr | xor_expr "^" and_expr\n or_expr ::= xor_expr | or_expr "|" xor_expr\n\nThe ``&`` operator yields the bitwise AND of its arguments, which must\nbe plain or long integers. The arguments are converted to a common\ntype.\n\nThe ``^`` operator yields the bitwise XOR (exclusive OR) of its\narguments, which must be plain or long integers. The arguments are\nconverted to a common type.\n\nThe ``|`` operator yields the bitwise (inclusive) OR of its arguments,\nwhich must be plain or long integers. The arguments are converted to\na common type.\n',
'bltin-code-objects':u'\nCode Objects\n************\n\nCode objects are used by the implementation to represent "pseudo-\ncompiled" executable Python code such as a function body. They differ\nfrom function objects because they don\'t contain a reference to their\nglobal execution environment. Code objects are returned by the built-\nin ``compile()`` function and can be extracted from function objects\nthrough their ``func_code`` attribute. See also the ``code`` module.\n\nA code object can be executed or evaluated by passing it (instead of a\nsource string) to the ``exec`` statement or the built-in ``eval()``\nfunction.\n\nSee *The standard type hierarchy* for more information.\n',
'bltin-ellipsis-object':u'\nThe Ellipsis Object\n*******************\n\nThis object is used by extended slice notation (see *Slicings*). It\nsupports no special operations. There is exactly one ellipsis object,\nnamed ``Ellipsis`` (a built-in name).\n\nIt is written as ``Ellipsis``.\n',
'bltin-file-objects':u'\nFile Objects\n************\n\nFile objects are implemented using C\'s ``stdio`` package and can be\ncreated with the built-in ``open()`` function. File objects are also\nreturned by some other built-in functions and methods, such as\n``os.popen()`` and ``os.fdopen()`` and the ``makefile()`` method of\nsocket objects. Temporary files can be created using the ``tempfile``\nmodule, and high-level file operations such as copying, moving, and\ndeleting files and directories can be achieved with the ``shutil``\nmodule.\n\nWhen a file operation fails for an I/O-related reason, the exception\n``IOError`` is raised. This includes situations where the operation\nis not defined for some reason, like ``seek()`` on a tty device or\nwriting a file opened for reading.\n\nFiles have the following methods:\n\nfile.close()\n\n Close the file. A closed file cannot be read or written any more.\n Any operation which requires that the file be open will raise a\n ``ValueError`` after the file has been closed. Calling ``close()``\n more than once is allowed.\n\n As of Python 2.5, you can avoid having to call this method\n explicitly if you use the ``with`` statement. For example, the\n following code will automatically close *f* when the ``with`` block\n is exited:\n\n from __future__ import with_statement # This isn\'t required in Python 2.6\n\n with open("hello.txt") as f:\n for line in f:\n print line\n\n In older versions of Python, you would have needed to do this to\n get the same effect:\n\n f = open("hello.txt")\n try:\n for line in f:\n print line\n finally:\n f.close()\n\n Note: Not all "file-like" types in Python support use as a context\n manager for the ``with`` statement. If your code is intended to\n work with any file-like object, you can use the function\n ``contextlib.closing()`` instead of using the object directly.\n\nfile.flush()\n\n Flush the internal buffer, like ``stdio``\'s ``fflush()``. This may\n be a no-op on some file-like objects.\n\n Note: ``flush()`` does not necessarily write the file\'s data to disk.\n Use ``flush()`` followed by ``os.fsync()`` to ensure this\n behavior.\n\nfile.fileno()\n\n Return the integer "file descriptor" that is used by the underlying\n implementation to request I/O operations from the operating system.\n This can be useful for other, lower level interfaces that use file\n descriptors, such as the ``fcntl`` module or ``os.read()`` and\n friends.\n\n Note: File-like objects which do not have a real file descriptor should\n *not* provide this method!\n\nfile.isatty()\n\n Return ``True`` if the file is connected to a tty(-like) device,\n else ``False``.\n\n Note: If a file-like object is not associated with a real file, this\n method should *not* be implemented.\n\nfile.next()\n\n A file object is its own iterator, for example ``iter(f)`` returns\n *f* (unless *f* is closed). When a file is used as an iterator,\n typically in a ``for`` loop (for example, ``for line in f: print\n line``), the ``next()`` method is called repeatedly. This method\n returns the next input line, or raises ``StopIteration`` when EOF\n is hit when the file is open for reading (behavior is undefined\n when the file is open for writing). In order to make a ``for``\n loop the most efficient way of looping over the lines of a file (a\n very common operation), the ``next()`` method uses a hidden read-\n ahead buffer. As a consequence of using a read-ahead buffer,\n combining ``next()`` with other file methods (like ``readline()``)\n does not work right. However, using ``seek()`` to reposition the\n file to an absolute position will flush the read-ahead buffer.\n\n New in version 2.3.\n\nfile.read([size])\n\n Read at most *size* bytes from the file (less if the read hits EOF\n before obtaining *size* bytes). If the *size* argument is negative\n or omitted, read all data until EOF is reached. The b
'bltin-null-object':u"\nThe Null Object\n***************\n\nThis object is returned by functions that don't explicitly return a\nvalue. It supports no special operations. There is exactly one null\nobject, named ``None`` (a built-in name).\n\nIt is written as ``None``.\n",
'bltin-type-objects':u"\nType Objects\n************\n\nType objects represent the various object types. An object's type is\naccessed by the built-in function ``type()``. There are no special\noperations on types. The standard module ``types`` defines names for\nall standard built-in types.\n\nTypes are written like this: ``<type 'int'>``.\n",
'booleans':u'\nBoolean operations\n******************\n\nBoolean operations have the lowest priority of all Python operations:\n\n expression ::= conditional_expression | lambda_form\n old_expression ::= or_test | old_lambda_form\n conditional_expression ::= or_test ["if" or_test "else" expression]\n or_test ::= and_test | or_test "or" and_test\n and_test ::= not_test | and_test "and" not_test\n not_test ::= comparison | "not" not_test\n\nIn the context of Boolean operations, and also when expressions are\nused by control flow statements, the following values are interpreted\nas false: ``False``, ``None``, numeric zero of all types, and empty\nstrings and containers (including strings, tuples, lists,\ndictionaries, sets and frozensets). All other values are interpreted\nas true. (See the ``__nonzero__()`` special method for a way to\nchange this.)\n\nThe operator ``not`` yields ``True`` if its argument is false,\n``False`` otherwise.\n\nThe expression ``x if C else y`` first evaluates *C* (*not* *x*); if\n*C* is true, *x* is evaluated and its value is returned; otherwise,\n*y* is evaluated and its value is returned.\n\nNew in version 2.5.\n\nThe expression ``x and y`` first evaluates *x*; if *x* is false, its\nvalue is returned; otherwise, *y* is evaluated and the resulting value\nis returned.\n\nThe expression ``x or y`` first evaluates *x*; if *x* is true, its\nvalue is returned; otherwise, *y* is evaluated and the resulting value\nis returned.\n\n(Note that neither ``and`` nor ``or`` restrict the value and type they\nreturn to ``False`` and ``True``, but rather return the last evaluated\nargument. This is sometimes useful, e.g., if ``s`` is a string that\nshould be replaced by a default value if it is empty, the expression\n``s or \'foo\'`` yields the desired value. Because ``not`` has to\ninvent a value anyway, it does not bother to return a value of the\nsame type as its argument, so e.g., ``not \'foo\'`` yields ``False``,\nnot ``\'\'``.)\n',
'break':u'\nThe ``break`` statement\n***********************\n\n break_stmt ::= "break"\n\n``break`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition\nwithin that loop.\n\nIt terminates the nearest enclosing loop, skipping the optional\n``else`` clause if the loop has one.\n\nIf a ``for`` loop is terminated by ``break``, the loop control target\nkeeps its current value.\n\nWhen ``break`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nleaving the loop.\n',
'callable-types':u'\nEmulating callable objects\n**************************\n\nobject.__call__(self[, args...])\n\n Called when the instance is "called" as a function; if this method\n is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n ``x.__call__(arg1, arg2, ...)``.\n',
'calls':u'\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 [","]\n | expression genexpr_for] ")"\n argument_list ::= positional_arguments ["," keyword_arguments]\n [",""*" expression] ["," keyword_arguments]\n [",""**" expression]\n | keyword_arguments [",""*" expression]\n [",""**" expression]\n | "*" expression [",""*" expression] [",""**" 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 certain class instances\nthemselves are callable; extensions may define additional callable\nobject types). All argument expressions are evaluated before the call\nis attempted. Please refer to section *Function definitions* for the\nsyntax 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\n**CPython implementation detail:** An implementation may provide\nbuilt-in functions whose positional parameters do not have names, even\nif they are \'named\' for the purpose of documentation, and which\ntherefore cannot be supplied by keyword. In CPython, this is the case\nfor functions implemented in C that use ``PyArg_ParseTuple()`` to\nparse 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
'class':u'\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= "class" classname [inheritance] ":" suite\n inheritance ::= "(" [expression_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. It first evaluates the\ninheritance list, if present. Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing. The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.) When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary. The class name is bound to this class object in the\noriginal local namespace.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by all instances. To create instance\nvariables, they can be set in a method with ``self.name = value``.\nBoth class and instance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results. For *new-style class*es, descriptors can\nbe used to create instance variables with different implementation\ndetails.\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions. The evaluation rules for the decorator\nexpressions are the same as for functions. The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n',
'coercion-rules':u"\nCoercion rules\n**************\n\nThis section used to document the rules for coercion. As the language\nhas evolved, the coercion rules have become hard to document\nprecisely; documenting what one version of one particular\nimplementation does is undesirable. Instead, here are some informal\nguidelines regarding coercion. In Python 3.0, coercion will not be\nsupported.\n\n* If the left operand of a % operator is a string or Unicode object,\n no coercion takes place and the string formatting operation is\n invoked instead.\n\n* It is no longer recommended to define a coercion operation. Mixed-\n mode operations on types that don't define coercion pass the\n original arguments to the operation.\n\n* New-style classes (those derived from ``object``) never invoke the\n ``__coerce__()`` method in response to a binary operator; the only\n time ``__coerce__()`` is invoked is when the built-in function\n ``coerce()`` is called.\n\n* For most intents and purposes, an operator that returns\n ``NotImplemented`` is treated the same as one that is not\n implemented at all.\n\n* Below, ``__op__()`` and ``__rop__()`` are used to signify the\n generic method names corresponding to an operator; ``__iop__()`` is\n used for the corresponding in-place operator. For example, for the\n operator '``+``', ``__add__()`` and ``__radd__()`` are used for the\n left and right variant of the binary operator, and ``__iadd__()``\n for the in-place variant.\n\n* For objects *x* and *y*, first ``x.__op__(y)`` is tried. If this is\n not implemented or returns ``NotImplemented``, ``y.__rop__(x)`` is\n tried. If this is also not implemented or returns\n ``NotImplemented``, a ``TypeError`` exception is raised. But see\n the following exception:\n\n* Exception to the previous item: if the left operand is an instance\n of a built-in type or a new-style class, and the right operand is an\n instance of a proper subclass of that type or class and overrides\n the base's ``__rop__()`` method, the right operand's ``__rop__()``\n method is tried *before* the left operand's ``__op__()`` method.\n\n This is done so that a subclass can completely override binary\n operators. Otherwise, the left operand's ``__op__()`` method would\n always accept the right operand: when an instance of a given class\n is expected, an instance of a subclass of that class is always\n acceptable.\n\n* When either operand type defines a coercion, this coercion is called\n before that type's ``__op__()`` or ``__rop__()`` method is called,\n but no sooner. If the coercion returns an object of a different\n type for the operand whose coercion is invoked, part of the process\n is redone using the new object.\n\n* When an in-place operator (like '``+=``') is used, if the left\n operand implements ``__iop__()``, it is invoked without any\n coercion. When the operation falls back to ``__op__()`` and/or\n ``__rop__()``, the normal coercion rules apply.\n\n* In ``x + y``, if *x* is a sequence that implements sequence\n concatenation, sequence concatenation is invoked.\n\n* In ``x * y``, if one operator is a sequence that implements sequence\n repetition, and the other is an integer (``int`` or ``long``),\n sequence repetition is invoked.\n\n* Rich comparisons (implemented by methods ``__eq__()`` and so on)\n never use coercion. Three-way comparison (implemented by\n ``__cmp__()``) does use coercion under the same conditions as other\n binary operations use it.\n\n* In the current implementation, the built-in numeric types ``int``,\n ``long`` and ``float`` do not use coercion; the type ``complex``\n however does use coercion for binary operators and rich comparisons,\n despite the above rules. The difference can become apparent when\n subclassing these types. Over time, the type ``complex`` may be\n fixed to avoid coercion. All these types implement a\n ``__coerce__()`` method, for use by the built-in ``coerce()``\n function.\n",
'comparisons':u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe forms ``<>`` and ``!=`` are equivalent; for consistency with C,\n``!=`` is preferred; where ``!=`` is mentioned below ``<>`` is also\naccepted. The ``<>`` spelling is considered obsolescent.\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects. The objects need not have the same type.\nIf both are numbers, they are converted to a common type. Otherwise,\nobjects of different types *always* compare unequal, and are ordered\nconsistently but arbitrarily. You can control comparison behavior of\nobjects of non-built-in types by defining a ``__cmp__`` method or rich\ncomparison methods like ``__gt__``, described in section *Special\nmethod names*.\n\n(This unusual definition of comparison was used to simplify the\ndefinition of operations like sorting and the ``in`` and ``not in``\noperators. In the future, the comparison rules for objects of\ndifferent types are likely to change.)\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n Unicode and 8-bit strings are fully interoperable in this behavior.\n [4]\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``cmp([1,2,x], [1,2,y])`` returns\n the same as ``cmp(x,y)``. If the corresponding element does not\n exist, the shorter sequence is ordered first (for example, ``[1,2] <\n [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if their sorted\n (key, value) lists compare equal. [5] Outcomes other than equality\n are resolved consistently, but are not otherwise defined. [6]\n\n* Most other objects of built-in types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nThe operators ``in`` and ``not in`` test for collection membership.\n``x in s`` evaluates to true if *x* is a member of the collection *s*,\nand false otherwise. ``x not in s`` returns the negation of ``x in\ns``. The collection membership test has traditionally been bound to\nsequences; an object is a member of a collection if the collection is\na sequence and contains an element equal to that object. However, it\nmake sense for many other object types to support membership tests\nwithout being a sequence. In particular, dictionaries (for keys) and\nsets support membership testing.\n\nFor the l
'compound':u'\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs. ``try`` specifies exception handlers and/or\ncleanup code for a group of statements. Function and class\ndefinitions are also syntactically compound statements.\n\nCompound statements consist of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n if test1: if test2: print x\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print`` statements are executed:\n\n if x < y < z: print x; print y; print z\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n | decorated\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else"":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else"":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expr
'context-managers':u'\nWith Statement Context Managers\n*******************************\n\nNew in version 2.5.\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code. Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The ``with``\n statement will bind this method\'s return value to the target(s)\n specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be ``None``.\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that ``__exit__()`` methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n',
'continue':u'\nThe ``continue`` statement\n**************************\n\n continue_stmt ::= "continue"\n\n``continue`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition or\n``finally`` clause within that loop. It continues with the next cycle\nof the nearest enclosing loop.\n\nWhen ``continue`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nstarting the next loop cycle.\n',
'conversions':u'\nArithmetic conversions\n**********************\n\nWhen a description of an arithmetic operator below uses the phrase\n"the numeric arguments are converted to a common type," the arguments\nare coerced using the coercion rules listed at *Coercion rules*. If\nboth arguments are standard numeric types, the following coercions are\napplied:\n\n* If either argument is a complex number, the other is converted to\n complex;\n\n* otherwise, if either argument is a floating point number, the other\n is converted to floating point;\n\n* otherwise, if either argument is a long integer, the other is\n converted to long integer;\n\n* otherwise, both must be plain integers and no conversion is\n necessary.\n\nSome additional rules apply for certain operators (e.g., a string left\nargument to the \'%\' operator). Extensions can define their own\ncoercions.\n',
'customization':u'\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_traceback`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.exc_traceback`` or ``sys.last_traceback``. Circular\n references which are garbage are detected when the option cycle\n detector is enabled (it\'s on by default), but can only be cleaned\n up if there are no Python-level ``__del__()`` methods involved.\n Refer to the documentation for the ``gc`` module for more\n information about how ``__del__()`` methods are hand
'debugger':u'\n``pdb`` --- The Python Debugger\n*******************************\n\nThe module ``pdb`` defines an interactive source code debugger for\nPython programs. It supports setting (conditional) breakpoints and\nsingle stepping at the source line level, inspection of stack frames,\nsource code listing, and evaluation of arbitrary Python code in the\ncontext of any stack frame. It also supports post-mortem debugging\nand can be called under program control.\n\nThe debugger is extensible --- it is actually defined as the class\n``Pdb``. This is currently undocumented but easily understood by\nreading the source. The extension interface uses the modules ``bdb``\n(undocumented) and ``cmd``.\n\nThe debugger\'s prompt is ``(Pdb)``. Typical usage to run a program\nunder control of the debugger is:\n\n >>> import pdb\n >>> import mymodule\n >>> pdb.run(\'mymodule.test()\')\n > <string>(0)?()\n (Pdb) continue\n > <string>(1)?()\n (Pdb) continue\n NameError: \'spam\'\n > <string>(1)?()\n (Pdb)\n\n``pdb.py`` can also be invoked as a script to debug other scripts.\nFor example:\n\n python -m pdb myscript.py\n\nWhen invoked as a script, pdb will automatically enter post-mortem\ndebugging if the program being debugged exits abnormally. After post-\nmortem debugging (or after normal exit of the program), pdb will\nrestart the program. Automatic restarting preserves pdb\'s state (such\nas breakpoints) and in most cases is more useful than quitting the\ndebugger upon program\'s exit.\n\nNew in version 2.4: Restarting post-mortem behavior added.\n\nThe typical usage to break into the debugger from a running program is\nto insert\n\n import pdb; pdb.set_trace()\n\nat the location you want to break into the debugger. You can then\nstep through the code following this statement, and continue running\nwithout the debugger using the ``c`` command.\n\nThe typical usage to inspect a crashed program is:\n\n >>> import pdb\n >>> import mymodule\n >>> mymodule.test()\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n File "./mymodule.py", line 4, in test\n test2()\n File "./mymodule.py", line 3, in test2\n print spam\n NameError: spam\n >>> pdb.pm()\n > ./mymodule.py(3)test2()\n -> print spam\n (Pdb)\n\nThe module defines the following functions; each enters the debugger\nin a slightly different way:\n\npdb.run(statement[, globals[, locals]])\n\n Execute the *statement* (given as a string) under debugger control.\n The debugger prompt appears before any code is executed; you can\n set breakpoints and type ``continue``, or you can step through the\n statement using ``step`` or ``next`` (all these commands are\n explained below). The optional *globals* and *locals* arguments\n specify the environment in which the code is executed; by default\n the dictionary of the module ``__main__`` is used. (See the\n explanation of the ``exec`` statement or the ``eval()`` built-in\n function.)\n\npdb.runeval(expression[, globals[, locals]])\n\n Evaluate the *expression* (given as a string) under debugger\n control. When ``runeval()`` returns, it returns the value of the\n expression. Otherwise this function is similar to ``run()``.\n\npdb.runcall(function[, argument, ...])\n\n Call the *function* (a function or method object, not a string)\n with the given arguments. When ``runcall()`` returns, it returns\n whatever the function call returned. The debugger prompt appears\n as soon as the function is entered.\n\npdb.set_trace()\n\n Enter the debugger at the calling stack frame. This is useful to\n hard-code a breakpoint at a given point in a program, even if the\n code is not otherwise being debugged (e.g. when an assertion\n fails).\n\npdb.post_mortem([traceback])\n\n Enter post-mortem debugging of the given *traceback* object. If no\n *traceback* is given, it uses the one of the exception that is\n currently being handled (an exception must be being handled if the\n default is to be used).\n\npdb.pm()\n\n En
'del':u'\nThe ``del`` statement\n*********************\n\n del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather that spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block. If the name is unbound, a\n``NameError`` exception will be raised.\n\nIt is illegal to delete a name from the local namespace if it occurs\nas a free variable in a nested block.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n',
'dict':u'\nDictionary displays\n*******************\n\nA dictionary display is a possibly empty series of key/datum pairs\nenclosed in curly braces:\n\n dict_display ::= "{" [key_datum_list] "}"\n key_datum_list ::= key_datum ("," key_datum)* [","]\n key_datum ::= expression ":" expression\n\nA dictionary display yields a new dictionary object.\n\nThe key/datum pairs are evaluated from left to right to define the\nentries of the dictionary: each key object is used as a key into the\ndictionary to store the corresponding datum.\n\nRestrictions on the types of the key values are listed earlier in\nsection *The standard type hierarchy*. (To summarize, the key type\nshould be *hashable*, which excludes all mutable objects.) Clashes\nbetween duplicate keys are not detected; the last datum (textually\nrightmost in the display) stored for a given key value prevails.\n',
'dynamic-features':u'\nInteraction with dynamic features\n*********************************\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- ``import *`` --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a ``SyntaxError``.\n\nIf ``exec`` is used in a function and the function contains or is a\nnested block with free variables, the compiler will raise a\n``SyntaxError`` unless the exec explicitly specifies the local\nnamespace for the ``exec``. (In other words, ``exec obj`` would be\nillegal, but ``exec obj in ns`` would be legal.)\n\nThe ``eval()``, ``execfile()``, and ``input()`` functions and the\n``exec`` statement do not have access to the full environment for\nresolving names. Names may be resolved in the local and global\nnamespaces of the caller. Free variables are not resolved in the\nnearest enclosing namespace, but in the global namespace. [1] The\n``exec`` statement and the ``eval()`` and ``execfile()`` functions\nhave optional arguments to override the global and local namespace.\nIf only one namespace is specified, it is used for both.\n',
'else':u'\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else"":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n',
'exceptions':u'\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\nExceptions can also be identified by strings, in which case the\n``except`` clause is selected by object identity. An arbitrary value\ncan be raised along with the identifying string which can be passed to\nthe handler.\n\nNote: Messages to exceptions are not part of the Python API. Their\n contents may change from one version of Python to the next without\n warning and should not be relied on by code which will run under\n multiple 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',
'exec':u'\nThe ``exec`` statement\n**********************\n\n exec_stmt ::= "exec" or_expr ["in" expression ["," expression]]\n\nThis statement supports dynamic execution of Python code. The first\nexpression should evaluate to either a string, an open file object, or\na code object. If it is a string, the string is parsed as a suite of\nPython statements which is then executed (unless a syntax error\noccurs). [1] If it is an open file, the file is parsed until EOF and\nexecuted. If it is a code object, it is simply executed. In all\ncases, the code that\'s executed is expected to be valid as file input\n(see section *File input*). Be aware that the ``return`` and\n``yield`` statements may not be used outside of function definitions\neven within the context of code passed to the ``exec`` statement.\n\nIn all cases, if the optional parts are omitted, the code is executed\nin the current scope. If only the first expression after ``in`` is\nspecified, it should be a dictionary, which will be used for both the\nglobal and the local variables. If two expressions are given, they\nare used for the global and local variables, respectively. If\nprovided, *locals* can be any mapping object.\n\nChanged in version 2.4: Formerly, *locals* was required to be a\ndictionary.\n\nAs a side effect, an implementation may insert additional keys into\nthe dictionaries given besides those corresponding to variable names\nset by the executed code. For example, the current implementation may\nadd a reference to the dictionary of the built-in module\n``__builtin__`` under the key ``__builtins__`` (!).\n\n**Programmer\'s hints:** dynamic evaluation of expressions is supported\nby the built-in function ``eval()``. The built-in functions\n``globals()`` and ``locals()`` return the current global and local\ndictionary, respectively, which may be useful to pass around for use\nby ``exec``.\n\n-[ Footnotes ]-\n\n[1] Note that the parser only accepts the Unix-style end of line\n convention. If you are reading the code from a file, make sure to\n use universal newline mode to convert Windows or Mac-style\n newlines.\n',
'execmodel':u'\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 file read by the\nbuilt-in function ``execfile()`` is a code block. The string argument\npassed to the built-in function ``eval()`` and to the ``exec``\nstatement is a code block. The expression read and evaluated by the\nbuilt-in function ``input()`` is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes generator expressions since\nthey are implemented using a function scope. This means that the\nfollowing will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nIf a name is bound in a block, it is a local variable of that block.\nIf a name is bound at the module level, it is a global variable. (The\nvariables of the module code block are local and global.) If a\nvariable is used in a code block but not defined there, it is a *free\nvariable*.\n\nWhen a name is not found at all, a ``NameError`` exception is raised.\nIf the name refers to a local variable that has not been bound, a\n``UnboundLocalError`` exception is raised. ``UnboundLocalError`` is a\nsubclass of ``NameError``.\n\nThe following constructs bind names: formal parameters to functions,\n``import`` statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, ``for`` loop header, in the\nsecond position of an ``except`` clause header or after ``as`` in a\n``with`` statement. The ``import`` statement of the form ``from ...\nimport *`` binds all names defined in the imported module, except\nthose beginning with an underscore. This form may only be used at the\nmodule 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 enti
'exprlists':u'\nExpression lists\n****************\n\n expression_list ::= expression ( "," expression )* [","]\n\nAn expression list containing at least one comma yields a tuple. The\nlength of the tuple is the number of expressions in the list. The\nexpressions are evaluated from left to right.\n\nThe trailing comma is required only to create a single tuple (a.k.a. a\n*singleton*); it is optional in all other cases. A single expression\nwithout a trailing comma doesn\'t create a tuple, but rather yields the\nvalue of that expression. (To create an empty tuple, use an empty pair\nof parentheses: ``()``.)\n',
'floating':u'\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 of floating point numbers can\nlook like octal integers, but are interpreted using radix 10. For\nexample, ``077e010`` is legal, and denotes the same number as\n``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':u'\nThe ``for`` statement\n*********************\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else"":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments, and then the suite is executed. When the items are\nexhausted (which is immediately when the sequence is empty), the suite\nin the ``else`` clause, if present, is executed, and the loop\nterminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nThe target list is not deleted when the loop is finished, but if the\nsequence is empty, it will not have been assigned to at all by the\nloop. Hint: the built-in function ``range()`` returns a sequence of\nintegers suitable to emulate the effect of Pascal\'s ``for i := a to b\ndo``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\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 internal\n counter is used to keep track of which item is used next, and this\n is incremented on each iteration. When this counter has reached the\n length of the sequence the loop terminates. This means that if the\n suite deletes the current (or a previous) item from the sequence,\n the next item will be skipped (since it gets the index of the\n current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n',
'formatstrings':u'\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 ::= (identifier | integer) ("." attribute_name | "[" element_index "]")*\n attribute_name ::= identifier\n element_index ::= integer | index_string\n index_string ::= <any source character except "]"> +\n conversion ::= "r" | "s"\n format_spec ::= <described in the next section>\n\nIn less formal terms, the replacement field starts with a\n*field_name*, which can either be a number (for a positional\nargument), or an identifier (for keyword arguments). Following this\nis an optional *conversion* field, which is preceded by an exclamation\npoint ``\'!\'``, and a *format_spec*, which is preceded by a colon\n``\':\'``.\n\nThe *field_name* itself begins with either a number or a keyword. If\nit\'s a number, it refers to a positional argument, and if it\'s a\nkeyword it refers to a named keyword argument. This can be followed\nby any number of index or attribute expressions. An expression of the\nform ``\'.name\'`` selects the named attribute using ``getattr()``,\nwhile an expression of the form ``\'[index]\'`` does an index lookup\nusing ``__getitem__()``.\n\nSome simple format string examples:\n\n"First, thou shalt count to {0}" # References first positional argument\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\nTwo conversion flags are currently supported: ``\'!s\'`` which calls\n``str()`` on the value, and ``\'!r\'`` which calls ``repr()``.\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 its\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 "
'function':u'\nFunction definitions\n********************\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n decorated ::= decorators (classdef | funcdef)\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n funcdef ::= "def" funcname "(" [parameter_list] ")"":" suite\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" identifier [, "**" identifier]\n | "**" identifier\n | defparameter [","] )\n defparameter ::= parameter ["=" expression]\n sublist ::= parameter ("," parameter)* [","]\n parameter ::= identifier | "(" sublist ")"\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code:\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to:\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more top-level parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters must also have a default value --- this is a syntactic\nrestriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *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
'global':u'\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**CPython implementation detail:** The current implementation does not\nenforce the latter two restrictions, but programs should not abuse\nthis freedom, as future implementations may enforce them or silently\nchange the meaning of the program.\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 an\n``exec`` statement does not affect the code block *containing* the\n``exec`` statement, and code contained in an ``exec`` statement is\nunaffected by ``global`` statements in the code containing the\n``exec`` statement. The same applies to the ``eval()``,\n``execfile()`` and ``compile()`` functions.\n',
'id-classes':u'\nReserved classes of identifiers\n*******************************\n\nCertain classes of identifiers (besides keywords) have special\nmeanings. These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n Not imported by ``from module import *``. The special identifier\n ``_`` is used in the interactive interpreter to store the result of\n the last evaluation; it is stored in the ``__builtin__`` module.\n When not in interactive mode, ``_`` has no special meaning and is\n not defined. See section *The import statement*.\n\n Note: The name ``_`` is often used in conjunction with\n internationalization; refer to the documentation for the\n ``gettext`` module for more information on this convention.\n\n``__*__``\n System-defined names. These names are defined by the interpreter\n and its implementation (including the standard library);\n applications should not expect to define additional names using\n this convention. The set of names of this class defined by Python\n may be extended in future versions. See section *Special method\n names*.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n',
'identifiers':u'\nIdentifiers and keywords\n************************\n\nIdentifiers (also referred to as *names*) are described by the\nfollowing lexical definitions:\n\n identifier ::= (letter|"_") (letter | digit | "_")*\n letter ::= lowercase | uppercase\n lowercase ::= "a"..."z"\n uppercase ::= "A"..."Z"\n digit ::= "0"..."9"\n\nIdentifiers are unlimited in length. Case is significant.\n\n\nKeywords\n========\n\nThe following identifiers are used as reserved words, or *keywords* of\nthe language, and cannot be used as ordinary identifiers. They must\nbe spelled exactly as written here:\n\n and del from not while\n as elif global or with\n assert else if pass yield\n break except import print\n class exec in raise\n continue finally is return\n def for lambda try\n\nChanged in version 2.4: ``None`` became a constant and is now\nrecognized by the compiler as a name for the built-in object ``None``.\nAlthough it is not a keyword, you cannot assign a different object to\nit.\n\nChanged in version 2.5: Both ``as`` and ``with`` are only recognized\nwhen the ``with_statement`` future feature has been enabled. It will\nalways be enabled in Python 2.6. See section *The with statement* for\ndetails. Note that using ``as`` and ``with`` as identifiers will\nalways issue a warning, even when the ``with_statement`` future\ndirective is not in effect.\n\n\nReserved classes of identifiers\n===============================\n\nCertain classes of identifiers (besides keywords) have special\nmeanings. These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n Not imported by ``from module import *``. The special identifier\n ``_`` is used in the interactive interpreter to store the result of\n the last evaluation; it is stored in the ``__builtin__`` module.\n When not in interactive mode, ``_`` has no special meaning and is\n not defined. See section *The import statement*.\n\n Note: The name ``_`` is often used in conjunction with\n internationalization; refer to the documentation for the\n ``gettext`` module for more information on this convention.\n\n``__*__``\n System-defined names. These names are defined by the interpreter\n and its implementation (including the standard library);\n applications should not expect to define additional names using\n this convention. The set of names of this class defined by Python\n may be extended in future versions. See section *Special method\n names*.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n',
'if':u'\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else"":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n',
'imaginary':u'\nImaginary literals\n******************\n\nImaginary literals are described by the following lexical definitions:\n\n imagnumber ::= (floatnumber | intpart) ("j" | "J")\n\nAn imaginary literal yields a complex number with a real part of 0.0.\nComplex numbers are represented as a pair of floating point numbers\nand have the same restrictions on their range. To create a complex\nnumber with a nonzero real part, add a floating point number to it,\ne.g., ``(3+4j)``. Some examples of imaginary literals:\n\n 3.14j 10.j 10j .001j 1e100j 3.14e-10j\n',
'import':u'\nThe ``import`` statement\n************************\n\n import_stmt ::= "import" module ["as" name] ( "," module ["as" name] )*\n | "from" relative_module "import" identifier ["as" name]\n ( "," identifier ["as" name] )*\n | "from" relative_module "import""(" identifier ["as" name]\n ( "," identifier ["as" name] )* [","] ")"\n | "from" module "import""*"\n module ::= (identifier ".")* identifier\n relative_module ::= "."* module | "."+\n name ::= identifier\n\nImport statements are executed in two steps: (1) find a module, and\ninitialize it if necessary; (2) define a name or names in the local\nnamespace (of the scope where the ``import`` statement occurs). The\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.\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_cach
'in':u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe forms ``<>`` and ``!=`` are equivalent; for consistency with C,\n``!=`` is preferred; where ``!=`` is mentioned below ``<>`` is also\naccepted. The ``<>`` spelling is considered obsolescent.\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects. The objects need not have the same type.\nIf both are numbers, they are converted to a common type. Otherwise,\nobjects of different types *always* compare unequal, and are ordered\nconsistently but arbitrarily. You can control comparison behavior of\nobjects of non-built-in types by defining a ``__cmp__`` method or rich\ncomparison methods like ``__gt__``, described in section *Special\nmethod names*.\n\n(This unusual definition of comparison was used to simplify the\ndefinition of operations like sorting and the ``in`` and ``not in``\noperators. In the future, the comparison rules for objects of\ndifferent types are likely to change.)\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n Unicode and 8-bit strings are fully interoperable in this behavior.\n [4]\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``cmp([1,2,x], [1,2,y])`` returns\n the same as ``cmp(x,y)``. If the corresponding element does not\n exist, the shorter sequence is ordered first (for example, ``[1,2] <\n [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if their sorted\n (key, value) lists compare equal. [5] Outcomes other than equality\n are resolved consistently, but are not otherwise defined. [6]\n\n* Most other objects of built-in types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nThe operators ``in`` and ``not in`` test for collection membership.\n``x in s`` evaluates to true if *x* is a member of the collection *s*,\nand false otherwise. ``x not in s`` returns the negation of ``x in\ns``. The collection membership test has traditionally been bound to\nsequences; an object is a member of a collection if the collection is\na sequence and contains an element equal to that object. However, it\nmake sense for many other object types to support membership tests\nwithout being a sequence. In particular, dictionaries (for keys) and\nsets support membership testing.\n\nFor the list and t
'integers':u'\nInteger and long integer literals\n*********************************\n\nInteger and long integer literals are described by the following\nlexical definitions:\n\n longinteger ::= integer ("l" | "L")\n integer ::= decimalinteger | octinteger | hexinteger | bininteger\n decimalinteger ::= nonzerodigit digit* | "0"\n octinteger ::= "0" ("o" | "O") octdigit+ | "0" octdigit+\n hexinteger ::= "0" ("x" | "X") hexdigit+\n bininteger ::= "0" ("b" | "B") bindigit+\n nonzerodigit ::= "1"..."9"\n octdigit ::= "0"..."7"\n bindigit ::= "0" | "1"\n hexdigit ::= digit | "a"..."f" | "A"..."F"\n\nAlthough both lower case ``\'l\'`` and upper case ``\'L\'`` are allowed as\nsuffix for long integers, it is strongly recommended to always use\n``\'L\'``, since the letter ``\'l\'`` looks too much like the digit\n``\'1\'``.\n\nPlain integer literals that are above the largest representable plain\ninteger (e.g., 2147483647 when using 32-bit arithmetic) are accepted\nas if they were long integers instead. [1] There is no limit for long\ninteger literals apart from what can be stored in available memory.\n\nSome examples of plain integer literals (first row) and long integer\nliterals (second and third rows):\n\n 7 2147483647 0177\n 3L 79228162514264337593543950336L 0377L 0x100000000L\n 79228162514264337593543950336 0xdeadbeef\n',
'lambda':u'\nLambdas\n*******\n\n lambda_form ::= "lambda" [parameter_list]: expression\n old_lambda_form ::= "lambda" [parameter_list]: old_expression\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 name(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.\n',
'lists':u'\nList displays\n*************\n\nA list display is a possibly empty series of expressions enclosed in\nsquare brackets:\n\n list_display ::= "[" [expression_list | list_comprehension] "]"\n list_comprehension ::= expression list_for\n list_for ::= "for" target_list "in" old_expression_list [list_iter]\n old_expression_list ::= old_expression [("," old_expression)+ [","]]\n list_iter ::= list_for | list_if\n list_if ::= "if" old_expression [list_iter]\n\nA list display yields a new list object. Its contents are specified\nby providing either a list of expressions or a list comprehension.\nWhen a comma-separated list of expressions is supplied, its elements\nare evaluated from left to right and placed into the list object in\nthat order. When a list comprehension is supplied, it consists of a\nsingle expression followed by at least one ``for`` clause and zero or\nmore ``for`` or ``if`` clauses. In this case, the elements of the new\nlist are those that would be produced by considering each of the\n``for`` or ``if`` clauses a block, nesting from left to right, and\nevaluating the expression to produce a list element each time the\ninnermost block is reached [1].\n',
'naming':u"\nNaming and binding\n******************\n\n*Names* refer to objects. Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block. A script\nfile (a file given as standard input to the interpreter or specified\non the interpreter command line the first argument) is a code block.\nA script command (a command specified on the interpreter command line\nwith the '**-c**' option) is a code block. The file read by the\nbuilt-in function ``execfile()`` is a code block. The string argument\npassed to the built-in function ``eval()`` and to the ``exec``\nstatement is a code block. The expression read and evaluated by the\nbuilt-in function ``input()`` is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block's execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes generator expressions since\nthey are implemented using a function scope. This means that the\nfollowing will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block's *environment*.\n\nIf a name is bound in a block, it is a local variable of that block.\nIf a name is bound at the module level, it is a global variable. (The\nvariables of the module code block are local and global.) If a\nvariable is used in a code block but not defined there, it is a *free\nvariable*.\n\nWhen a name is not found at all, a ``NameError`` exception is raised.\nIf the name refers to a local variable that has not been bound, a\n``UnboundLocalError`` exception is raised. ``UnboundLocalError`` is a\nsubclass of ``NameError``.\n\nThe following constructs bind names: formal parameters to functions,\n``import`` statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, ``for`` loop header, in the\nsecond position of an ``except`` clause header or after ``as`` in a\n``with`` statement. The ``import`` statement of the form ``from ...\nimport *`` binds all names defined in the imported module, except\nthose beginning with an underscore. This form may only be used at the\nmodule 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\noperat
'numbers':u"\nNumeric literals\n****************\n\nThere are four types of numeric literals: plain integers, long\nintegers, floating point numbers, and imaginary numbers. There are no\ncomplex literals (complex numbers can be formed by adding a real\nnumber and an imaginary 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':u'\nEmulating numeric types\n***********************\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``//``, ``%``, ``divmod()``,\n ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``). For\n instance, to evaluate the expression ``x + y``, where *x* is an\n instance of a class that has an ``__add__()`` method,\n ``x.__add__(y)`` is called. The ``__divmod__()`` method should be\n the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n should not be related to ``__truediv__()`` (described below). Note\n that ``__pow__()`` should be defined to accept an optional third\n argument if the ternary version of the built-in ``pow()`` function\n is to be supported.\n\n If one of those methods does not support the operation with the\n supplied arguments, it should return ``NotImplemented``.\n\nobject.__div__(self, other)\nobject.__truediv__(self, other)\n\n The division operator (``/``) is implemented by these methods. The\n ``__truediv__()`` method is used when ``__future__.division`` is in\n effect, otherwise ``__div__()`` is used. If only one of these two\n methods is defined, the object will not support division in the\n alternate context; ``TypeError`` will be raised instead.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rdiv__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``%``, ``divmod()``,\n ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``) with\n reflected (swapped) operands. These functions are only called if\n the left operand does not support the corresponding operation and\n the operands are of different types. [3] For instance, to evaluate\n the expression ``x - y``, where *y* is an instance of a class that\n has an ``__rsub__()`` method, ``y.__rsub__(x)`` is called if\n ``x.__sub__(y)`` returns *NotImplemented*.\n\n Note that ternary ``pow()`` will not try calling ``__rpow__()``\n (the coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left operand\'s\n type and that subclass provides the reflected method for the\n operation, this method will be called before the left operand\'s\n non-reflected method. This behavior allows subclasses to\n override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__idiv__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n These methods are called to implement the augmented arithmetic\n assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``). These methods\n should attempt to do the operation in-place (modifyi
'objects':u'\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.\n\n**CPython implementation detail:** 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 provides a convenient way to do\nthis.\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\
'operator-summary':u'\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 [8] |\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...}``, ```expressions...``` | display, dictionary display, string |\n| | conversion |\n+-------------------------------------------------+---------------------------------------+\n\n-[ Fo
'pass':u'\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':u'\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. The result type is that of the\narguments after coercion.\n\nWith mixed operand types, the coercion rules for binary arithmetic\noperators apply. For int and long int operands, the result has the\nsame type as the operands (after coercion) unless the second argument\nis negative; in that case, all arguments are converted to float and a\nfloat result is delivered. For example, ``10**2`` returns ``100``, but\n``10**-2`` returns ``0.01``. (This last feature was added in Python\n2.2. In Python 2.1 and before, if both arguments were of integer types\nand the second argument was negative, an exception was raised).\n\nRaising ``0.0`` to a negative power results in a\n``ZeroDivisionError``. Raising a negative number to a fractional power\nresults in a ``ValueError``.\n',
'print':u'\nThe ``print`` statement\n***********************\n\n print_stmt ::= "print" ([expression ("," expression)* [","]]\n | ">>" expression [("," expression)+ [","]])\n\n``print`` evaluates each expression in turn and writes the resulting\nobject to standard output (see below). If an object is not a string,\nit is first converted to a string using the rules for string\nconversions. The (resulting or original) string is then written. A\nspace is written before each object is (converted and) written, unless\nthe output system believes it is positioned at the beginning of a\nline. This is the case (1) when no characters have yet been written\nto standard output, (2) when the last character written to standard\noutput is a whitespace character except ``\'\'``, or (3) when the last\nwrite operation on standard output was not a ``print`` statement. (In\nsome cases it may be functional to write an empty string to standard\noutput for this reason.)\n\nNote: Objects which act like file objects but which are not the built-in\n file objects often do not properly emulate this aspect of the file\n object\'s behavior, so it is best not to rely on this.\n\nA ``\'\\n\'`` character is written at the end, unless the ``print``\nstatement ends with a comma. This is the only action if the statement\ncontains just the keyword ``print``.\n\nStandard output is defined as the file object named ``stdout`` in the\nbuilt-in module ``sys``. If no such object exists, or if it does not\nhave a ``write()`` method, a ``RuntimeError`` exception is raised.\n\n``print`` also has an extended form, defined by the second portion of\nthe syntax described above. This form is sometimes referred to as\n"``print`` chevron." In this form, the first expression after the\n``>>`` must evaluate to a "file-like" object, specifically an object\nthat has a ``write()`` method as described above. With this extended\nform, the subsequent expressions are printed to this file object. If\nthe first expression evaluates to ``None``, then ``sys.stdout`` is\nused as the file for output.\n',
'raise':u'\nThe ``raise`` statement\n***********************\n\n raise_stmt ::= "raise" [expression ["," expression ["," 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 expressions to get three objects,\nusing ``None`` as the value of omitted expressions. The first two\nobjects are used to determine the *type* and *value* of the exception.\n\nIf the first object is an instance, the type of the exception is the\nclass of the instance, the instance itself is the value, and the\nsecond object must be ``None``.\n\nIf the first object is a class, it becomes the type of the exception.\nThe second object is used to determine the exception value: If it is\nan instance of the class, the instance becomes the exception value. If\nthe second object is a tuple, it is used as the argument list for the\nclass constructor; if it is ``None``, an empty argument list is used,\nand any other object is treated as a single argument to the\nconstructor. The instance so created by calling the constructor is\nused as the exception value.\n\nIf a third object is present and not ``None``, it must be a traceback\nobject (see section *The standard type hierarchy*), and it is\nsubstituted instead of the current location as the place where the\nexception occurred. If the third object is present and not a\ntraceback object or ``None``, a ``TypeError`` exception is raised.\nThe three-expression form of ``raise`` is useful to re-raise an\nexception transparently in an except clause, but ``raise`` with no\nexpressions should be preferred if the exception to be re-raised was\nthe most recently active exception in the current scope.\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',
'return':u'\nThe ``return`` statement\n************************\n\n return_stmt ::= "return" [expression_list]\n\n``return`` may only occur syntactically nested in a function\ndefinition, not within a nested class definition.\n\nIf an expression list is present, it is evaluated, else ``None`` is\nsubstituted.\n\n``return`` leaves the current function call with the expression list\n(or ``None``) as return value.\n\nWhen ``return`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nleaving the function.\n\nIn a generator function, the ``return`` statement is not allowed to\ninclude an **expression_list**. In that context, a bare ``return``\nindicates that the generator is done and will cause ``StopIteration``\nto be raised.\n',
'sequence-methods':u'\nAdditional methods for emulation of sequence types\n**************************************************\n\nThe following optional methods can be defined to further emulate\nsequence objects. Immutable sequences methods should at most only\ndefine ``__getslice__()``; mutable sequences might define all three\nmethods.\n\nobject.__getslice__(self, i, j)\n\n Deprecated since version 2.0: Support slice objects as parameters\n to the ``__getitem__()`` method. (However, built-in types in\n CPython currently still implement ``__getslice__()``. Therefore,\n you have to override it in derived classes when implementing\n slicing.)\n\n Called to implement evaluation of ``self[i:j]``. The returned\n object should be of the same type as *self*. Note that missing *i*\n or *j* in the slice expression are replaced by zero or\n ``sys.maxint``, respectively. If negative indexes are used in the\n slice, the length of the sequence is added to that index. If the\n instance does not implement the ``__len__()`` method, an\n ``AttributeError`` is raised. No guarantee is made that indexes\n adjusted this way are not still negative. Indexes which are\n greater than the length of the sequence are not modified. If no\n ``__getslice__()`` is found, a slice object is created instead, and\n passed to ``__getitem__()`` instead.\n\nobject.__setslice__(self, i, j, sequence)\n\n Called to implement assignment to ``self[i:j]``. Same notes for *i*\n and *j* as for ``__getslice__()``.\n\n This method is deprecated. If no ``__setslice__()`` is found, or\n for extended slicing of the form ``self[i:j:k]``, a slice object is\n created, and passed to ``__setitem__()``, instead of\n ``__setslice__()`` being called.\n\nobject.__delslice__(self, i, j)\n\n Called to implement deletion of ``self[i:j]``. Same notes for *i*\n and *j* as for ``__getslice__()``. This method is deprecated. If no\n ``__delslice__()`` is found, or for extended slicing of the form\n ``self[i:j:k]``, a slice object is created, and passed to\n ``__delitem__()``, instead of ``__delslice__()`` being called.\n\nNotice that these methods are only invoked when a single slice with a\nsingle colon is used, and the slice method is available. For slice\noperations involving extended slice notation, or in absence of the\nslice methods, ``__getitem__()``, ``__setitem__()`` or\n``__delitem__()`` is called with a slice object as argument.\n\nThe following example demonstrate how to make your program or module\ncompatible with earlier versions of Python (assuming that methods\n``__getitem__()``, ``__setitem__()`` and ``__delitem__()`` support\nslice objects as arguments):\n\n class MyClass:\n ...\n def __getitem__(self, index):\n ...\n def __setitem__(self, index, value):\n ...\n def __delitem__(self, index):\n ...\n\n if sys.version_info < (2, 0):\n # They won\'t be defined if version is at least 2.0 final\n\n def __getslice__(self, i, j):\n return self[max(0, i):max(0, j):]\n def __setslice__(self, i, j, seq):\n self[max(0, i):max(0, j):] = seq\n def __delslice__(self, i, j):\n del self[max(0, i):max(0, j):]\n ...\n\nNote the calls to ``max()``; these are necessary because of the\nhandling of negative indices before the ``__*slice__()`` methods are\ncalled. When negative indexes are used, the ``__*item__()`` methods\nreceive them as provided, but the ``__*slice__()`` methods get a\n"cooked" form of the index values. For each negative index value, the\nlength of the sequence is added to the index before calling the method\n(which may still result in a negative index); this is the customary\nhandling of negative indexes by the built-in sequence types, and the\n``__*item__()`` methods are expected to do this as well. However,\nsince they should already be doing that, negative indexes cannot be\npassed in; they must be constrained to the bounds of the sequence\nbefore being pas
'sequence-types':u"\nEmulating container types\n*************************\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well. The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. (For backwards compatibility, the method\n``__getslice__()`` (see below) can also be defined to handle simple,\nbut not extended slices.) It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``has_key()``,\n``get()``, ``clear()``, ``setdefault()``, ``iterkeys()``,\n``itervalues()``, ``iteritems()``, ``pop()``, ``popitem()``,\n``copy()``, and ``update()`` behaving similar to those for Python's\nstandard dictionary objects. The ``UserDict`` module provides a\n``DictMixin`` class to help create those methods from a base set of\n``__getitem__()``, ``__setitem__()``, ``__delitem__()``, and\n``keys()``. Mutable sequences should provide methods ``append()``,\n``count()``, ``index()``, ``extend()``, ``insert()``, ``pop()``,\n``remove()``, ``reverse()`` and ``sort()``, like Python standard list\nobjects. Finally, sequence types should implement addition (meaning\nconcatenation) and multiplication (meaning repetition) by defining the\nmethods ``__add__()``, ``__radd__()``, ``__iadd__()``, ``__mul__()``,\n``__rmul__()`` and ``__imul__()`` described below; they should not\ndefine ``__coerce__()`` or other numerical operators. It is\nrecommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should be equivalent of ``has_key()``;\nfor sequences, it should search through the values. It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``iterkeys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n Called to implement the built-in function ``len()``. Should return\n the length of the object, an integer ``>=`` 0. Also, an object\n that doesn't define a ``__nonzero__()`` method and whose\n ``__len__()`` method returns zero is considered to be false in a\n Boolean context.\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of ``self[key]``. For sequence\n types, the accepted keys should be integers and slice objects.\n Note that the special interpretation of negative indexes (if the\n class wishes to emulate a sequence type) is up to the\n ``__getitem__()`` method. If *key* is of an inappropriate type,\n ``TypeError`` may be raised; if of a value outside the set of\n indexes for the sequence (after any special interpretation of\n negative values), ``IndexError`` should be raised. For mapping\n types, if *key* is missing (not in the container), ``KeyError``\n should be raised.\n\n Note: ``for`` loops expect that an ``IndexError`` will be raised for\n illegal indexes to allow proper detection of the end of the\n sequence.\n\nobject.__setitem__(self, key, value)\n\n Called to implement assignment to ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support changes to the values for keys, or if new keys\n can be added, or for sequences if elements can be replaced. The\n same exceptions should be raised for improper *key* values as for\n the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n Called to implement deletion of ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support removal of keys, or for sequences if elements\n can be
'shifting':u'\nShifting operations\n*******************\n\nThe shifting operations have lower priority than the arithmetic\noperations:\n\n shift_expr ::= a_expr | shift_expr ( "<<" | ">>" ) a_expr\n\nThese operators accept plain or long integers as arguments. The\narguments are converted to a common type. They shift the first\nargument to the left or right by the number of bits given by the\nsecond argument.\n\nA right shift by *n* bits is defined as division by ``pow(2, n)``. A\nleft shift by *n* bits is defined as multiplication with ``pow(2,\nn)``. Negative shift counts raise a ``ValueError`` exception.\n',
'slicings':u'\nSlicings\n********\n\nA slicing selects a range of items in a sequence object (e.g., a\nstring, tuple or list). Slicings may be used as expressions or as\ntargets in assignment or ``del`` statements. The syntax for a\nslicing:\n\n slicing ::= simple_slicing | extended_slicing\n simple_slicing ::= primary "[" short_slice "]"\n extended_slicing ::= primary "[" slice_list "]"\n slice_list ::= slice_item ("," slice_item)* [","]\n slice_item ::= expression | proper_slice | ellipsis\n proper_slice ::= short_slice | long_slice\n short_slice ::= [lower_bound] ":" [upper_bound]\n long_slice ::= short_slice ":" [stride]\n lower_bound ::= expression\n upper_bound ::= expression\n stride ::= expression\n ellipsis ::= "..."\n\nThere is ambiguity in the formal syntax here: anything that looks like\nan expression list also looks like a slice list, so any subscription\ncan be interpreted as a slicing. Rather than further complicating the\nsyntax, this is disambiguated by defining that in this case the\ninterpretation as a subscription takes priority over the\ninterpretation as a slicing (this is the case if the slice list\ncontains no proper slice nor ellipses). Similarly, when the slice\nlist has exactly one short slice and no trailing comma, the\ninterpretation as a simple slicing takes priority over that as an\nextended slicing.\n\nThe semantics for a simple slicing are as follows. The primary must\nevaluate to a sequence object. The lower and upper bound expressions,\nif present, must evaluate to plain integers; defaults are zero and the\n``sys.maxint``, respectively. If either bound is negative, the\nsequence\'s length is added to it. The slicing now selects all items\nwith index *k* such that ``i <= k < j`` where *i* and *j* are the\nspecified lower and upper bounds. This may be an empty sequence. It\nis not an error if *i* or *j* lie outside the range of valid indexes\n(such items don\'t exist so they aren\'t selected).\n\nThe semantics for an extended slicing are as follows. The primary\nmust evaluate to a mapping object, and it is indexed with a key that\nis constructed from the slice list, as follows. If the slice list\ncontains at least one comma, the key is a tuple containing the\nconversion of the slice items; otherwise, the conversion of the lone\nslice item is the key. The conversion of a slice item that is an\nexpression is that expression. The conversion of an ellipsis slice\nitem is the built-in ``Ellipsis`` object. The conversion of a proper\nslice is a slice object (see section *The standard type hierarchy*)\nwhose ``start``, ``stop`` and ``step`` attributes are the values of\nthe expressions given as lower bound, upper bound and stride,\nrespectively, substituting ``None`` for missing expressions.\n',
'specialattrs':u"\nSpecial Attributes\n******************\n\nThe implementation adds a few special read-only attributes to several\nobject types, where they are relevant. Some of these are not reported\nby the ``dir()`` built-in function.\n\nobject.__dict__\n\n A dictionary or other mapping object used to store an object's\n (writable) attributes.\n\nobject.__methods__\n\n Deprecated since version 2.2: Use the built-in function ``dir()``\n to get a list of an object's attributes. This attribute is no\n longer available.\n\nobject.__members__\n\n Deprecated since version 2.2: Use the built-in function ``dir()``\n to get a list of an object's attributes. This attribute is no\n longer available.\n\ninstance.__class__\n\n The class to which a class instance belongs.\n\nclass.__bases__\n\n The tuple of base classes of a class object. If there are no base\n classes, this will be an empty tuple.\n\nclass.__name__\n\n The name of the class or type.\n\nThe following attributes are only supported by *new-style class*es.\n\nclass.__mro__\n\n This attribute is a tuple of classes that are considered when\n looking for base classes during method resolution.\n\nclass.mro()\n\n This method can be overridden by a metaclass to customize the\n method resolution order for its instances. It is called at class\n instantiation, and its result is stored in ``__mro__``.\n\nclass.__subclasses__()\n\n Each new-style class keeps a list of weak references to its\n immediate subclasses. This method returns a list of all those\n references still alive. Example:\n\n >>> int.__subclasses__()\n [<type 'bool'>]\n\n-[ Footnotes ]-\n\n[1] Additional information on these special methods may be found in\n the Python Reference Manual (*Basic customization*).\n\n[2] As a consequence, the list ``[1, 2]`` is considered equal to\n ``[1.0, 2.0]``, and similarly for tuples.\n\n[3] They must have since the parser can't tell the type of the\n operands.\n\n[4] To format only a tuple you should therefore provide a singleton\n tuple whose only element is the tuple to be formatted.\n\n[5] These numbers are fairly arbitrary. They are intended to avoid\n printing endless strings of meaningless digits without hampering\n correct use and without having to know the exact precision of\n floating point values on a particular machine.\n\n[6] The advantage of leaving the newline on is that returning an empty\n string is then an unambiguous EOF indication. It is also possible\n (in cases where it might matter, for example, if you want to make\n an exact copy of a file while scanning its lines) to tell whether\n the last line of a file ended in a newline or not (yes this\n happens!).\n",
'specialnames':u'\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators. For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``x.__getitem__(i)`` for\nold-style classes and ``type(x).__getitem__(x, i)`` for new-style\nclasses. Except where mentioned, attempts to execute an operation\nraise an exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled. For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense. (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\nBasic customization\n===================\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count rea
'string-conversions':u'\nString conversions\n******************\n\nA string conversion is an expression list enclosed in reverse (a.k.a.\nbackward) quotes:\n\n string_conversion ::= "\'" expression_list "\'"\n\nA string conversion evaluates the contained expression list and\nconverts the resulting object into a string according to rules\nspecific to its type.\n\nIf the object is a string, a number, ``None``, or a tuple, list or\ndictionary containing only objects whose type is one of these, the\nresulting string is a valid Python expression which can be passed to\nthe built-in function ``eval()`` to yield an expression with the same\nvalue (or an approximation, if floating point numbers are involved).\n\n(In particular, converting a string adds quotes around it and converts\n"funny" characters to escape sequences that are safe to print.)\n\nRecursive objects (for example, lists or dictionaries that contain a\nreference to themselves, directly or indirectly) use ``...`` to\nindicate a recursive reference, and the result cannot be passed to\n``eval()`` to get an equal value (``SyntaxError`` will be raised\ninstead).\n\nThe built-in function ``repr()`` performs exactly the same conversion\nin its argument as enclosing it in parentheses and reverse quotes\ndoes. The built-in function ``str()`` performs a similar but more\nuser-friendly conversion.\n',
'string-methods':u'\nString Methods\n**************\n\nBelow are listed the string methods which both 8-bit strings and\nUnicode objects support. Note that none of these methods take keyword\narguments.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, unicode, list, tuple,\nbuffer, xrange* section. To output formatted strings use template\nstrings or the ``%`` operator described in the *String Formatting\nOperations* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n Return a copy of the string with only its first character\n capitalized.\n\n For 8-bit strings, this method is locale-dependent.\n\nstr.center(width[, fillchar])\n\n Return centered in a string of length *width*. Padding is done\n using the specified *fillchar* (default is a space).\n\n Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.count(sub[, start[, end]])\n\n Return the number of non-overlapping occurrences of substring *sub*\n in the range [*start*, *end*]. Optional arguments *start* and\n *end* are interpreted as in slice notation.\n\nstr.decode([encoding[, errors]])\n\n Decodes the string using the codec registered for *encoding*.\n *encoding* defaults to the default string encoding. *errors* may\n be given to set a different error handling scheme. The default is\n ``\'strict\'``, meaning that encoding errors raise ``UnicodeError``.\n Other possible values are ``\'ignore\'``, ``\'replace\'`` and any other\n name registered via ``codecs.register_error()``, see section *Codec\n Base Classes*.\n\n New in version 2.2.\n\n Changed in version 2.3: Support for other error handling schemes\n added.\n\nstr.encode([encoding[, errors]])\n\n Return an encoded version of the string. Default encoding is the\n current default string encoding. *errors* may be given to set a\n different error handling scheme. The default for *errors* is\n ``\'strict\'``, meaning that encoding errors raise a\n ``UnicodeError``. Other possible values are ``\'ignore\'``,\n ``\'replace\'``, ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and\n any other name registered via ``codecs.register_error()``, see\n section *Codec Base Classes*. For a list of possible encodings, see\n section *Standard Encodings*.\n\n New in version 2.0.\n\n Changed in version 2.3: Support for ``\'xmlcharrefreplace\'`` and\n ``\'backslashreplace\'`` and other error handling schemes added.\n\nstr.endswith(suffix[, start[, end]])\n\n Return ``True`` if the string ends with the specified *suffix*,\n otherwise return ``False``. *suffix* can also be a tuple of\n suffixes to look for. With optional *start*, test beginning at\n that position. With optional *end*, stop comparing at that\n position.\n\n Changed in version 2.5: Accept tuples as *suffix*.\n\nstr.expandtabs([tabsize])\n\n Return a copy of the string where all tab characters are replaced\n by one or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the range [*start*, *end*].\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\nstr.format(*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\
'strings':u'\nString literals\n***************\n\nString literals are described by the following lexical definitions:\n\n stringliteral ::= [stringprefix](shortstring | longstring)\n stringprefix ::= "r" | "u" | "ur" | "R" | "U" | "UR" | "Ur" | "uR"\n shortstring ::= "\'" shortstringitem* "\'" | \'"\' shortstringitem* \'"\'\n longstring ::= "\'\'\'" longstringitem* "\'\'\'"\n | \'"""\' longstringitem* \'"""\'\n shortstringitem ::= shortstringchar | escapeseq\n longstringitem ::= longstringchar | escapeseq\n shortstringchar ::= <any source character except "\\" or newline or the quote>\n longstringchar ::= <any source character except "\\">\n escapeseq ::= "\\" <any ASCII character>\n\nOne syntactic restriction not indicated by these productions is that\nwhitespace is not allowed between the **stringprefix** and the rest of\nthe string literal. The source character set is defined by the\nencoding declaration; it is ASCII if no encoding declaration is given\nin the source file; see section *Encoding declarations*.\n\nIn plain English: String literals can be enclosed in matching single\nquotes (``\'``) or double quotes (``"``). They can also be enclosed in\nmatching groups of three single or double quotes (these are generally\nreferred to as *triple-quoted strings*). The backslash (``\\``)\ncharacter is used to escape characters that otherwise have a special\nmeaning, such as newline, backslash itself, or the quote character.\nString literals may optionally be prefixed with a letter ``\'r\'`` or\n``\'R\'``; such strings are called *raw strings* and use different rules\nfor interpreting backslash escape sequences. A prefix of ``\'u\'`` or\n``\'U\'`` makes the string a Unicode string. Unicode strings use the\nUnicode character set as defined by the Unicode Consortium and ISO\n10646. Some additional escape sequences, described below, are\navailable in Unicode strings. The two prefix characters may be\ncombined; in this case, ``\'u\'`` must appear before ``\'r\'``.\n\nIn triple-quoted strings, unescaped newlines and quotes are allowed\n(and are retained), except that three unescaped quotes in a row\nterminate the string. (A "quote" is the character used to open the\nstring, i.e. either ``\'`` or ``"``.)\n\nUnless an ``\'r\'`` or ``\'R\'`` prefix is present, escape sequences in\nstrings are interpreted according to rules similar to those used by\nStandard C. The recognized escape sequences are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence | Meaning | Notes |\n+===================+===================================+=========+\n| ``\\newline`` | Ignored | |\n+-------------------+-----------------------------------+---------+\n| ``\\\\`` | Backslash (``\\``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\\'`` | Single quote (``\'``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\"`` | Double quote (``"``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\a`` | ASCII Bell (BEL) | |\n+-------------------+-----------------------------------+---------+\n| ``\\b`` | ASCII Backspace (BS) | |\n+-------------------+-----------------------------------+---------+\n| ``\\f`` | ASCII Formfeed (FF) | |\n+-------------------+-----------------------------------+---------+\n| ``\\n`` | ASCII Linefeed (LF) | |\n+-------------------+-----------------------------------+---------+\n| ``\\N{name}`` | Character named *name* in the | |\n| | Unicode database (Unicode only) | |\n+-------------------+-----------------------------------+---------+\n| ``\\r`` | ASCII Carriage Return (CR) |
'subscriptions':u'\nSubscriptions\n*************\n\nA subscription selects an item of a sequence (string, tuple or list)\nor mapping (dictionary) object:\n\n subscription ::= primary "[" expression_list "]"\n\nThe primary must evaluate to an object of a sequence or mapping type.\n\nIf the primary is a mapping, the expression list must evaluate to an\nobject whose value is one of the keys of the mapping, and the\nsubscription selects the value in the mapping that corresponds to that\nkey. (The expression list is a tuple except if it has exactly one\nitem.)\n\nIf the primary is a sequence, the expression (list) must evaluate to a\nplain integer. If this value is negative, the length of the sequence\nis added to it (so that, e.g., ``x[-1]`` selects the last item of\n``x``.) The resulting value must be a nonnegative integer less than\nthe number of items in the sequence, and the subscription selects the\nitem whose index is that value (counting from zero).\n\nA string\'s items are characters. A character is not a separate data\ntype but a string of exactly one character.\n',
'truth':u"\nTruth Value Testing\n*******************\n\nAny object can be tested for truth value, for use in an ``if`` or\n``while`` condition or as operand of the Boolean operations below. The\nfollowing values are considered false:\n\n* ``None``\n\n* ``False``\n\n* zero of any numeric type, for example, ``0``, ``0L``, ``0.0``,\n ``0j``.\n\n* any empty sequence, for example, ``''``, ``()``, ``[]``.\n\n* any empty mapping, for example, ``{}``.\n\n* instances of user-defined classes, if the class defines a\n ``__nonzero__()`` or ``__len__()`` method, when that method returns\n the integer zero or ``bool`` value ``False``. [1]\n\nAll other values are considered true --- so objects of many types are\nalways true.\n\nOperations and built-in functions that have a Boolean result always\nreturn ``0`` or ``False`` for false and ``1`` or ``True`` for true,\nunless otherwise stated. (Important exception: the Boolean operations\n``or`` and ``and`` always return one of their operands.)\n",
'try':u'\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try"":" suite\n ("except" [expression [("as" | ",") target]] ":" suite)+\n ["else"":" suite]\n ["finally"":" suite]\n try2_stmt ::= "try"":" suite\n"finally"":" suite\n\nChanged in version 2.5: In previous versions of Python,\n``try``...``except``...``finally`` did not work. ``try``...``except``\nhad to be nested in ``try``...``finally``.\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object, a tuple containing an item compatible with the\nexception, or, in the (deprecated) case of string exceptions, is the\nraised string itself (note that the object identities must match, i.e.\nit must be the same string object, not just a string with the same\nvalue).\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified in that except clause, if present, and the except\nclause\'s suite is executed. All except clauses must have an\nexecutable block. When the end of this block is reached, execution\ncontinues normally after the entire try statement. (This means that\nif two nested handlers exist for the same exception, and the exception\noccurs in the try clause of the inner handler, the outer handler will\nnot handle the exception.)\n\nBefore an except clause\'s suite is executed, details about the\nexception are assigned to three variables in the ``sys`` module:\n``sys.exc_type`` receives the object identifying the exception;\n``sys.exc_value`` receives the exception\'s parameter;\n``sys.exc_traceback`` receives a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. These details are also available through the\n``sys.exc_info()`` function, which returns a tuple ``(exc_type,\nexc_value, exc_traceback)``. Use of the corresponding variables is\ndeprecated in favor of this function, since their use is unsafe in a\nthreaded program. As of Python 1.5, the variables are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the sav
'types':u'\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python. Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types. Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.).\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\' These are attributes that provide access to the\nimplementation and are not intended for general use. Their definition\nmay change in the future.\n\nNone\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name ``None``.\n It is used to signify the absence of a value in many situations,\n e.g., it is returned from functions that don\'t explicitly return\n anything. Its truth value is false.\n\nNotImplemented\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name\n ``NotImplemented``. Numeric methods and rich comparison methods may\n return this value if they do not implement the operation for the\n operands provided. (The interpreter will then try the reflected\n operation, or some other fallback, depending on the operator.) Its\n truth value is true.\n\nEllipsis\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name\n ``Ellipsis``. It is used to indicate the presence of the ``...``\n syntax in a slice. Its truth value is true.\n\n``numbers.Number``\n These are created by numeric literals and returned as results by\n arithmetic operators and arithmetic built-in functions. Numeric\n objects are immutable; once created their value never changes.\n Python numbers are of course strongly related to mathematical\n numbers, but subject to the limitations of numerical representation\n in computers.\n\n Python distinguishes between integers, floating point numbers, and\n complex numbers:\n\n ``numbers.Integral``\n These represent elements from the mathematical set of integers\n (positive and negative).\n\n There are three types of integers:\n\n Plain integers\n These represent numbers in the range -2147483648 through\n 2147483647. (The range may be larger on machines with a\n larger natural word size, but not smaller.) When the result\n of an operation would fall outside this range, the result is\n normally returned as a long integer (in some cases, the\n exception ``OverflowError`` is raised instead). For the\n purpose of shift and mask operations, integers are assumed to\n have a binary, 2\'s complement notation using 32 or more bits,\n and hiding no bits from the user (i.e., all 4294967296\n different bit patterns correspond to different values).\n\n Long integers\n These represent numbers in an unlimited range, subject to\n available (virtual) memory only. For the purpose of shift\n and mask operations, a binary representation is assumed, and\n negative numbers are represented in a variant of 2\'s\n complement which gives the illusion of an infinite string of\n sign bits extending to the left.\n\n Booleans\n These represent the truth values False and True. The two\n objects representing the values False and True are the only\n Boolean objects. The Boolean type is a subtype of plain\n integers, and Boolean values behave like the values 0 and 1,\n respectively, in almost all contexts, the exception being\n that when converted to a string, the strings ``"False"`` or\n ``"True"`` are returned, respectively.\n\n The rules for integer representation are intended to give the\n most meaningful interpretation of shift and mask operations\n involving negative integers
'typesfunctions':u'\nFunctions\n*********\n\nFunction objects are created by function definitions. The only\noperation on a function object is to call it: ``func(argument-list)``.\n\nThere are really two flavors of function objects: built-in functions\nand user-defined functions. Both support the same operation (to call\nthe function), but the implementation is different, hence the\ndifferent object types.\n\nSee *Function definitions* for more information.\n',
'typesmapping':u'\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects. There is currently only one standard\nmapping type, the *dictionary*. (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values. Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys. Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry. (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass 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 is\n specified both in the positional argument and as a keyword\n argument, the value associated with the keyword is retained in the\n dictionary. For example, these all return a dictionary equal to\n ``{"one": 2, "two": 3}``:\n\n * ``dict(one=2, two=3)``\n\n * ``dict({\'one\': 2, \'two\': 3})``\n\n * ``dict(zip((\'one\', \'two\'), (2, 3)))``\n\n * ``dict([[\'two\', 3], [\'one\', 2]])``\n\n The first example only works for keys that are valid Python\n identifiers; the others work with any valid keys.\n\n New in version 2.2.\n\n Changed in version 2.3: Support for building a dictionary from\n keyword arguments added.\n\n These are the operations that dictionaries support (and therefore,\n custom mapping types should support too):\n\n len(d)\n\n Return the number of items in the dictionary *d*.\n\n d[key]\n\n Return the item of *d* with key *key*. Raises a ``KeyError`` if\n *key* is not in the map.\n\n New in version 2.5: If a subclass of dict defines a method\n ``__missing__()``, if the key *key* is not present, the\n ``d[key]`` operation calls that method with the key *key* as\n argument. The ``d[key]`` operation then returns or raises\n whatever is returned or raised by the ``__missing__(key)`` call\n if the key is not present. No other operations or methods invoke\n ``__missing__()``. If ``__missing__()`` is not defined,\n ``KeyError`` is raised. ``__missing__()`` must be a method; it\n cannot be an instance variable. For an example, see\n ``collections.defaultdict``.\n\n d[key] = value\n\n Set ``d[key]`` to *value*.\n\n del d[key]\n\n Remove ``d[key]`` from *d*. Raises a ``KeyError`` if *key* is\n not in the map.\n\n key in d\n\n Return ``True`` if *d* has a key *key*, else ``False``.\n\n New in version 2.2.\n\n key not in d\n\n Equivalent to ``not key in d``.\n\n
'typesmethods':u"\nMethods\n*******\n\nMethods are functions that are called using the attribute notation.\nThere are two flavors: built-in methods (such as ``append()`` on\nlists) and class instance methods. Built-in methods are described\nwith the types that support them.\n\nThe implementation adds two special read-only attributes to class\ninstance methods: ``m.im_self`` is the object on which the method\noperates, and ``m.im_func`` is the function implementing the method.\nCalling ``m(arg-1, arg-2, ..., arg-n)`` is completely equivalent to\ncalling ``m.im_func(m.im_self, arg-1, arg-2, ..., arg-n)``.\n\nClass instance methods are either *bound* or *unbound*, referring to\nwhether the method was accessed through an instance or a class,\nrespectively. When a method is unbound, its ``im_self`` attribute\nwill be ``None`` and if called, an explicit ``self`` object must be\npassed as the first argument. In this case, ``self`` must be an\ninstance of the unbound method's class (or a subclass of that class),\notherwise a ``TypeError`` is raised.\n\nLike function objects, methods objects support getting arbitrary\nattributes. However, since method attributes are actually stored on\nthe underlying function object (``meth.im_func``), setting method\nattributes on either bound or unbound methods is disallowed.\nAttempting to set a method attribute results in a ``TypeError`` being\nraised. In order to set a method attribute, you need to explicitly\nset it on the underlying function object:\n\n class C:\n def method(self):\n pass\n\n c = C()\n c.method.im_func.whoami = 'my name is c'\n\nSee *The standard type hierarchy* for more information.\n",
'typesmodules':u"\nModules\n*******\n\nThe only special operation on a module is attribute access:\n``m.name``, where *m* is a module and *name* accesses a name defined\nin *m*'s symbol table. Module attributes can be assigned to. (Note\nthat the ``import`` statement is not, strictly speaking, an operation\non a module object; ``import foo`` does not require a module object\nnamed *foo* to exist, rather it requires an (external) *definition*\nfor a module named *foo* somewhere.)\n\nA special member of every module is ``__dict__``. This is the\ndictionary containing the module's symbol table. Modifying this\ndictionary will actually change the module's symbol table, but direct\nassignment to the ``__dict__`` attribute is not possible (you can\nwrite ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but\nyou can't write ``m.__dict__ = {}``). Modifying ``__dict__`` directly\nis not recommended.\n\nModules built into the interpreter are written like this: ``<module\n'sys' (built-in)>``. If loaded from a file, they are written as\n``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.\n",
'typesseq':u'\nSequence Types --- ``str``, ``unicode``, ``list``, ``tuple``, ``buffer``, ``xrange``\n************************************************************************************\n\nThere are six sequence types: strings, Unicode strings, lists, tuples,\nbuffers, and xrange objects.\n\nFor other containers see the built in ``dict`` and ``set`` classes,\nand the ``collections`` module.\n\nString literals are written in single or double quotes: ``\'xyzzy\'``,\n``"frobozz"``. See *String literals* for more about string literals.\nUnicode strings are much like strings, but are specified in the syntax\nusing a preceding ``\'u\'`` character: ``u\'abc\'``, ``u"def"``. In\naddition to the functionality described here, there are also string-\nspecific methods described in the *String Methods* section. Lists are\nconstructed with square brackets, separating items with commas: ``[a,\nb, c]``. Tuples are constructed by the comma operator (not within\nsquare brackets), with or without enclosing parentheses, but an empty\ntuple must have the enclosing parentheses, such as ``a, b, c`` or\n``()``. A single item tuple must have a trailing comma, such as\n``(d,)``.\n\nBuffer objects are not directly supported by Python syntax, but can be\ncreated by calling the built-in function ``buffer()``. They don\'t\nsupport concatenation or repetition.\n\nObjects of type xrange are similar to buffers in that there is no\nspecific syntax to create them, but they are created using the\n``xrange()`` function. They don\'t support slicing, concatenation or\nrepetition, and using ``in``, ``not in``, ``min()`` or ``max()`` on\nthem is inefficient.\n\nMost sequence types support the following operations. The ``in`` and\n``not in`` operations have the same priorities as the comparison\noperations. The ``+`` and ``*`` operations have the same priority as\nthe corresponding numeric operations. [3] Additional methods are\nprovided for *Mutable Sequence Types*.\n\nThis table lists the sequence operations sorted in ascending priority\n(operations in the same box have the same priority). In the table,\n*s* and *t* are sequences of the same type; *n*, *i* and *j* are\nintegers:\n\n+--------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+====================+==================================+============+\n| ``x in s`` | ``True`` if an item of *s* is | (1) |\n| | equal to *x*, else ``False`` | |\n+--------------------+----------------------------------+------------+\n| ``x not in s`` | ``False`` if an item of *s* is | (1) |\n| | equal to *x*, else ``True`` | |\n+--------------------+----------------------------------+------------+\n| ``s + t`` | the concatenation of *s* and *t* | (6) |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s`` | *n* shallow copies of *s* | (2) |\n| | concatenated | |\n+--------------------+----------------------------------+------------+\n| ``s[i]`` | *i*\'th item of *s*, origin 0 | (3) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]`` | slice of *s* from *i* to *j* | (3)(4) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]`` | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+--------------------+----------------------------------+------------+\n| ``len(s)`` | length of *s* | |\n+--------------------+----------------------------------+------------+\n| ``min(s)`` | smallest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``max(s)`` | largest item of *s* | |\n+--------------------+----------
'typesseq-mutable':u"\nMutable Sequence Types\n**********************\n\nList objects support additional operations that allow in-place\nmodification of the object. Other mutable sequence types (when added\nto the language) should also support these operations. Strings and\ntuples are immutable sequence types: such objects cannot be modified\nonce created. The following operations are defined on mutable sequence\ntypes (where *x* is an arbitrary object):\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation | Result | Notes |\n+================================+==================================+=======================+\n| ``s[i] = x`` | item *i* of *s* is replaced by | |\n| | *x* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t`` | slice of *s* from *i* to *j* is | |\n| | replaced by the contents of the | |\n| | iterable *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]`` | same as ``s[i:j] = []`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t`` | the elements of ``s[i:j:k]`` are | (1) |\n| | replaced by those of *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]`` | removes the elements of | |\n| | ``s[i:j:k]`` from the list | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)`` | same as ``s[len(s):len(s)] = | (2) |\n| | [x]`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)`` | same as ``s[len(s):len(s)] = x`` | (3) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)`` | return number of *i*'s for which | |\n| | ``s[i] == x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])`` | return smallest *k* such that | (4) |\n| | ``s[k] == x`` and ``i <= k < j`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)`` | same as ``s[i:i] = [x]`` | (5) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])`` | same as ``x = s[i]; del s[i]; | (6) |\n| | return x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)`` | same as ``del s[s.index(x)]`` | (4) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()`` | reverses the items of *s* in | (7) |\n| | place | |\n+--------------------
'unary':u'\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\nplain or long integer argument. The bitwise inversion of ``x`` is\ndefined as ``-(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':u'\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',
'with':u'\nThe ``with`` statement\n**********************\n\nNew in version 2.5.\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" expression ["as" target] ":" suite\n\nThe execution of the ``with`` statement proceeds as follows:\n\n1. The context expression is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__enter__()`` method is invoked.\n\n3. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 5 below.\n\n4. The suite is executed.\n\n5. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nNote: In Python 2.5, the ``with`` statement is only allowed when the\n ``with_statement`` feature has been enabled. It is always enabled\n in Python 2.6.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n',
'yield':u'\nThe ``yield`` statement\n***********************\n\n yield_stmt ::= yield_expression\n\nThe ``yield`` statement is only used when defining a generator\nfunction, and is only used in the body of the generator function.\nUsing a ``yield`` statement in a function definition is sufficient to\ncause that definition to create a generator function instead of a\nnormal function.\n\nWhen a generator function is called, it returns an iterator known as a\ngenerator iterator, or more commonly, a generator. The body of the\ngenerator function is executed by calling the generator\'s ``next()``\nmethod repeatedly until it raises an exception.\n\nWhen a ``yield`` statement is executed, the state of the generator is\nfrozen and the value of **expression_list** is returned to\n``next()``\'s caller. By "frozen" we mean that all local state is\nretained, including the current bindings of local variables, the\ninstruction pointer, and the internal evaluation stack: enough\ninformation is saved so that the next time ``next()`` is invoked, the\nfunction can proceed exactly as if the ``yield`` statement were just\nanother external call.\n\nAs of Python version 2.5, the ``yield`` statement is now allowed in\nthe ``try`` clause of a ``try`` ... ``finally`` construct. If the\ngenerator is not resumed before it is finalized (by reaching a zero\nreference count or by being garbage collected), the generator-\niterator\'s ``close()`` method will be called, allowing any pending\n``finally`` clauses to execute.\n\nNote: In Python 2.2, the ``yield`` statement was only allowed when the\n ``generators`` feature has been enabled. This ``__future__`` import\n statement was used to enable the feature:\n\n from __future__ import generators\n\nSee also:\n\n **PEP 0255** - Simple Generators\n The proposal for adding generators and the ``yield`` statement\n to Python.\n\n **PEP 0342** - Coroutines via Enhanced Generators\n The proposal that, among other generator enhancements, proposed\n allowing ``yield`` to appear inside a ``try`` ... ``finally``\n block.\n'}
