Lines Matching refs:particular
20 'comparisons': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe 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 tuple types, ``x in y`` is true if and only if there\nexists an index *i* such that ``x == y[i]`` is true.\n\nFor the Unicode and string types, ``x in y`` is true if and only if\n*x* is a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nNote, *x* and *y* need not be the same type; consequently, ``u\'ab\' in\n\'abc\'`` will return ``True``. Empty strings are always considered to\nbe a substring of any other string, so ``"" in "abc"`` will return\n``True``.\n\nChanged in version 2.3: Previously, *x* was required to be a string of\nlength ``1``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` but do\ndefine ``__iter__()``, ``x in y`` is true if some value ``z`` with ``x\n== z`` is produced while iterating over ``y``. If an exception is\nraised during the iteration, it is as if ``in`` raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n``__getitem__()``, ``x in y`` is true if and only if there is a non-\nnegative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [7]\n',
38 'global': '\nThe ``global`` statement\n************************\n\n global_stmt ::= "global" identifier ("," identifier)*\n\nThe ``global`` statement is a declaration which holds for the entire\ncurrent code block. It means that the listed identifiers are to be\ninterpreted as globals. It would be impossible to assign to a global\nvariable without ``global``, although free variables may refer to\nglobals without being declared global.\n\nNames listed in a ``global`` statement must not be used in the same\ncode block textually preceding that ``global`` statement.\n\nNames listed in a ``global`` statement must not be defined as formal\nparameters or in a ``for`` loop control target, ``class`` definition,\nfunction definition, or ``import`` statement.\n\n**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',
43 particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python. The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language. It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n future_statement ::= "from" "__future__" "import" feature ["as" name]\n ("," feature ["as" name])*\n | "from" "__future__" "import" "(" feature ["as" name]\n ("," feature ["as" name])* [","] ")"\n feature ::= identifier\n name ::= identifier\n\nA future statement must appear near the top of the module. The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 2.6 are ``unicode_literals``,\n``print_function``, ``absolute_import``, ``division``, ``generators``,\n``nested_scopes`` and ``with_statement``. ``generators``,\n``with_statement``, ``nested_scopes`` are redundant in Python version\n2.6 and above because they are always enabled.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code. It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently. Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by an ``exec`` statement or calls to the built-in\nfunctions ``compile()`` and ``execfile()`` that occur in a module\n``M`` containing a future statement will, by default, use the new\nsyntax or semantics associated with the future statement. This can,\nstarting with Python 2.2 be controlled by optional arguments to\n``compile()`` --- see the documentation of that function for details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session. If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\nSee also:\n\n **PEP 236** - Back to the __future__\n The original proposal for the __future__ mechanism.\n',
44 'in': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe 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 tuple types, ``x in y`` is true if and only if there\nexists an index *i* such that ``x == y[i]`` is true.\n\nFor the Unicode and string types, ``x in y`` is true if and only if\n*x* is a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nNote, *x* and *y* need not be the same type; consequently, ``u\'ab\' in\n\'abc\'`` will return ``True``. Empty strings are always considered to\nbe a substring of any other string, so ``"" in "abc"`` will return\n``True``.\n\nChanged in version 2.3: Previously, *x* was required to be a string of\nlength ``1``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` but do\ndefine ``__iter__()``, ``x in y`` is true if some value ``z`` with ``x\n== z`` is produced while iterating over ``y``. If an exception is\nraised during the iteration, it is as if ``in`` raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n``__getitem__()``, ``x in y`` is true if and only if there is a non-\nnegative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [7]\n',
61 particularhat does not define a\n ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n Called to implement the unary arithmetic operations (``-``, ``+``,\n ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__long__(self)\nobject.__float__(self)\n\n Called to implement the built-in functions ``complex()``,\n ``int()``, ``long()``, and ``float()``. Should return a value of\n the appropriate type.\n\nobject.__oct__(self)\nobject.__hex__(self)\n\n Called to implement the built-in functions ``oct()`` and ``hex()``.\n Should return a string value.\n\nobject.__index__(self)\n\n Called to implement ``operator.index()``. Also called whenever\n Python needs an integer object (such as in slicing). Must return\n an integer (int or long).\n\n New in version 2.5.\n\nobject.__coerce__(self, other)\n\n Called to implement "mixed-mode" numeric arithmetic. Should either\n return a 2-tuple containing *self* and *other* converted to a\n common numeric type, or ``None`` if conversion is impossible. When\n the common type would be the type of ``other``, it is sufficient to\n return ``None``, since the interpreter will also ask the other\n object to attempt a coercion (but sometimes, if the implementation\n of the other type cannot be changed, it is useful to do the\n conversion to the other type here). A return value of\n ``NotImplemented`` is equivalent to returning ``None``.\n\n\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
67 ost of the attributes labelled "Writable" check the type of the\n assigned value.\n\n Changed in version 2.4: ``func_name`` is now writable.\n\n Function objects also support getting and setting arbitrary\n attributes, which can be used, for example, to attach metadata\n to functions. Regular attribute dot-notation is used to get and\n set such attributes. *Note that the current implementation only\n supports function attributes on user-defined functions. Function\n attributes on built-in functions may be supported in the\n future.*\n\n Additional information about a function\'s definition can be\n retrieved from its code object; see the description of internal\n types below.\n\n User-defined methods\n A user-defined method object combines a class, a class instance\n (or ``None``) and any callable object (normally a user-defined\n function).\n\n Special read-only attributes: ``im_self`` is the class instance\n object, ``im_func`` is the function object; ``im_class`` is the\n class of ``im_self`` for bound methods or the class that asked\n for the method for unbound methods; ``__doc__`` is the method\'s\n documentation (same as ``im_func.__doc__``); ``__name__`` is the\n method name (same as ``im_func.__name__``); ``__module__`` is\n the name of the module the method was defined in, or ``None`` if\n unavailable.\n\n Changed in version 2.2: ``im_self`` used to refer to the class\n that defined the method.\n\n Changed in version 2.6: For Python 3 forward-compatibility,\n ``im_func`` is also available as ``__func__``, and ``im_self``\n as ``__self__``.\n\n Methods also support accessing (but not setting) the arbitrary\n function attributes on the underlying function object.\n\n User-defined method objects may be created when getting an\n attribute of a class (perhaps via an instance of that class), if\n that attribute is a user-defined function object, an unbound\n user-defined method object, or a class method object. When the\n attribute is a user-defined method object, a new method object\n is only created if the class from which it is being retrieved is\n the same as, or a derived class of, the class stored in the\n original method object; otherwise, the original method object is\n used as it is.\n\n When a user-defined method object is created by retrieving a\n user-defined function object from a class, its ``im_self``\n attribute is ``None`` and the method object is said to be\n unbound. When one is created by retrieving a user-defined\n function object from a class via one of its instances, its\n ``im_self`` attribute is the instance, and the method object is\n said to be bound. In either case, the new method\'s ``im_class``\n attribute is the class from which the retrieval takes place, and\n its ``im_func`` attribute is the original function object.\n\n When a user-defined method object is created by retrieving\n another method object from a class or instance, the behaviour is\n the same as for a function object, except that the ``im_func``\n attribute of the new instance is not the original method object\n but its ``im_func`` attribute.\n\n When a user-defined method object is created by retrieving a\n class method object from a class or instance, its ``im_self``\n attribute is the class itself, and its ``im_func`` attribute is\n the function object underlying the class method.\n\n When an unbound user-defined method object is called, the\n underlying function (``im_func``) is called, with the\n restriction that the first argument must be an instance of the\n proper class (``im_class``) or of a derived class thereof.\n\n When a bound user-defined method object is called, the\n underlying function (``im_func``) is called, inserting the class\n instance (``im_self``) in front of the argument list. For\n instance, when ``C`` is a class which contains a definition for\n a function ``f()``, and ``x`` is an instance of ``C``, calling\n ``x.f(1)`` is equivalent to calling ``C.f(x, 1)``.\n\n When a user-defined method object is derived from a class method\n object, the "class instance" stored in ``im_self`` will actually\n be the class itself, so that calling either ``x.f(1)`` or\n ``C.f(1)`` is equivalent to calling ``f(C,1)`` where ``f`` is\n the underlying function.\n\n Note that the transformation from function object to (unbound or\n bound) method object happens each time the attribute is\n retrieved from the class or instance. In some cases, a fruitful\n optimization is to assign the attribute to a local variable and\n call that local variable. Also notice that this transformation\n only happens for user-defined functions; other callable objects\n (and all non-callable objects) are retrieved without\n transformation. It is also important to note that user-defined\n functions which are attributes of a class instance are not\n converted to bound methods; this *only* happens when the\n function is an attribute of the class.\n\n Generator functions\n A function or method which uses the ``yield`` statement (see\n section *The yield statement*) is called a *generator function*.\n Such a function, when called, always returns an iterator object\n which can be used to execute the body of the function: calling\n the iterator\'s ``next()`` method will cause the function to\n execute until it provides a value using the ``yield`` statement.\n When the function executes a ``return`` statement or falls off\n the end, a ``StopIteration`` exception is raised and the\n iterator will have reached the end of the set of values to be\n returned.\n\n Built-in functions\n A built-in function object is a wrapper around a C function.\n Examples of built-in functions are ``len()`` and ``math.sin()``\n (``math`` is a standard built-in module). The number and type of\n the arguments are determined by the C function. Special read-\n only attributes: ``__doc__`` is the function\'s documentation\n string, or ``None`` if unavailable; ``__name__`` is the\n function\'s name; ``__self__`` is set to ``None`` (but see the\n next item); ``__module__`` is the name of the module the\n function was defined in or ``None`` if unavailable.\n\n Built-in methods\n This is really a different disguise of a built-in function, this\n time containing an object passed to the C function as an\n implicit extra argument. An example of a built-in method is\n ``alist.append()``, assuming *alist* is a list object. In this\n case, the special read-only attribute ``__self__`` is set to the\n object denoted by *alist*.\n\n Class Types\n Class types, or "new-style classes," are callable. These\n objects normally act as factories for new instances of\n themselves, but variations are possible for class types that\n override ``__new__()``. The arguments of the call are passed to\n ``__new__()`` and, in the typical case, to ``__init__()`` to\n initialize the new instance.\n\n Classic Classes\n Class objects are described below. When a class object is\n called, a new class instance (also described below) is created\n and returned. This implies a call to the class\'s ``__init__()``\n method if it has one. Any arguments are passed on to the\n ``__init__()`` method. If there is no ``__init__()`` method,\n the class must be called without arguments.\n\n Class instances\n Class instances are described below. Class instances are\n callable only when the class has a ``__call__()`` method;\n ``x(arguments)`` is a shorthand for ``x.__call__(arguments)``.\n\nModules\n Modules are imported by the ``import`` statement (see section *The\n import statement*). A module object has a namespace implemented by\n a dictionary object (this is the dictionary referenced by the\n func_globals attribute of functions defined in the module).\n Attribute references are translated to lookups in this dictionary,\n e.g., ``m.x`` is equivalent to ``m.__dict__["x"]``. A module object\n does not contain the code object used to initialize the module\n (since it isn\'t needed once the initialization is done).\n\n Attribute assignment updates the module\'s namespace dictionary,\n e.g., ``m.x = 1`` is equivalent to ``m.__dict__["x"] = 1``.\n\n Special read-only attribute: ``__dict__`` is the module\'s namespace\n as a dictionary object.\n\n **CPython implementation detail:** Because of the way CPython\n clears module dictionaries, the module dictionary will be cleared\n when the module falls out of scope even if the dictionary still has\n live references. To avoid this, copy the dictionary or keep the\n module around while using its dictionary directly.\n\n Predefined (writable) attributes: ``__name__`` is the module\'s\n name; ``__doc__`` is the module\'s documentation string, or ``None``\n if unavailable; ``__file__`` is the pathname of the file from which\n the module was loaded, if it was loaded from a file. The\n ``__file__`` attribute is not present for C modules that are\n statically linked into the interpreter; for extension modules\n loaded dynamically from a shared library, it is the pathname of the\n shared library file.\n\nClasses\n Both class types (new-style classes) and class objects (old-\n style/classic classes) are typically created by class definitions\n (see section *Class definitions*). A class has a namespace\n implemented by a dictionary object. Class attribute references are\n translated to lookups in this dictionary, e.g., ``C.x`` is\n translated to ``C.__dict__["x"]`` (although for new-style classes\n in particularparticular feature enabled: bit\n ``0x2000`` is set if the function was compiled with future\n division enabled; bits ``0x10`` and ``0x1000`` were used in\n earlier versions of Python.\n\n Other bits in ``co_flags`` are reserved for internal use.\n\n If a code object represents a function, the first item in\n ``co_consts`` is the documentation string of the function, or\n ``None`` if undefined.\n\n Frame objects\n Frame objects represent execution frames. They may occur in\n traceback objects (see below).\n\n Special read-only attributes: ``f_back`` is to the previous\n stack frame (towards the caller), or ``None`` if this is the\n bottom stack frame; ``f_code`` is the code object being executed\n in this frame; ``f_locals`` is the dictionary used to look up\n local variables; ``f_globals`` is used for global variables;\n ``f_builtins`` is used for built-in (intrinsic) names;\n ``f_restricted`` is a flag indicating whether the function is\n executing in restricted execution mode; ``f_lasti`` gives the\n precise instruction (this is an index into the bytecode string\n of the code object).\n\n Special writable attributes: ``f_trace``, if not ``None``, is a\n function called at the start of each source code line (this is\n used by the debugger); ``f_exc_type``, ``f_exc_value``,\n ``f_exc_traceback`` represent the last exception raised in the\n parent frame provided another exception was ever raised in the\n current frame (in all other cases they are None); ``f_lineno``\n is the current line number of the frame --- writing to this from\n within a trace function jumps to the given line (only for the\n bottom-most frame). A debugger can implement a Jump command\n (aka Set Next Statement) by writing to f_lineno.\n\n Traceback objects\n Traceback objects represent a stack trace of an exception. A\n traceback object is created when an exception occurs. When the\n search for an exception handler unwinds the execution stack, at\n each unwound level a traceback object is inserted in front of\n the current traceback. When an exception handler is entered,\n the stack trace is made available to the program. (See section\n *The try statement*.) It is accessible as ``sys.exc_traceback``,\n and also as the third item of the tuple returned by\n ``sys.exc_info()``. The latter is the preferred interface,\n since it works correctly when the program is using multiple\n threads. When the program contains no suitable handler, the\n stack trace is written (nicely formatted) to the standard error\n stream; if the interpreter is interactive, it is also made\n available to the user as ``sys.last_traceback``.\n\n Special read-only attributes: ``tb_next`` is the next level in\n the stack trace (towards the frame where the exception\n occurred), or ``None`` if there is no next level; ``tb_frame``\n points to the execution frame of the current level;\n ``tb_lineno`` gives the line number where the exception\n occurred; ``tb_lasti`` indicates the precise instruction. The\n line number and last instruction in the traceback may differ\n from the line number of its frame object if the exception\n occurred in a ``try`` statement with no matching except clause\n or with a finally clause.\n\n Slice objects\n Slice objects are used to represent slices when *extended slice\n syntax* is used. This is a slice using two colons, or multiple\n slices or ellipses separated by commas, e.g., ``a[i:j:step]``,\n ``a[i:j, k:l]``, or ``a[..., i:j]``. They are also created by\n the built-in ``slice()`` function.\n\n Special read-only attributes: ``start`` is the lower bound;\n ``stop`` is the upper bound; ``step`` is the step value; each is\n ``None`` if omitted. These attributes can have any type.\n\n Slice objects support one method:\n\n slice.indices(self, length)\n\n This method takes a single integer argument *length* and\n computes information about the extended slice that the slice\n object would describe if applied to a sequence of *length*\n items. It returns a tuple of three integers; respectively\n these are the *start* and *stop* indices and the *step* or\n stride length of the slice. Missing or out-of-bounds indices\n are handled in a manner consistent with regular slices.\n\n New in version 2.3.\n\n Static method objects\n Static method objects provide a way of defeating the\n transformation of function objects to method objects described\n above. A static method object is a wrapper around any other\n object, usually a user-defined method object. When a static\n method object is retrieved from a class or a class instance, the\n object actually returned is the wrapped object, which is not\n subject to any further transformation. Static method objects are\n not themselves callable, although the objects they wrap usually\n are. Static method objects are created by the built-in\n ``staticmethod()`` constructor.\n\n Class method objects\n A class method object, like a static method object, is a wrapper\n around another object that alters the way in which that object\n is retrieved from classes and class instances. The behaviour of\n class method objects upon such retrieval is described above,\n under "User-defined methods". Class method objects are created\n by the built-in ``classmethod()`` constructor.\n',
72 'typesseq': '\nSequence Types --- ``str``, ``unicode``, ``list``, ``tuple``, ``bytearray``, ``buffer``, ``xrange``\n***************************************************************************************************\n\nThere are seven sequence types: strings, Unicode strings, lists,\ntuples, bytearrays, buffers, and xrange objects.\n\nFor other containers see the built in ``dict`` and ``set`` classes,\nand the ``collections`` module.\n\nString literals are written in single or double quotes: ``\'xyzzy\'``,\n``"frobozz"``. See *String literals* for more about string literals.\nUnicode strings are much like strings, but are specified in the syntax\nusing a preceding ``\'u\'`` character: ``u\'abc\'``, ``u"def"``. In\naddition to the functionality described here, there are also string-\nspecific methods described in the *String Methods* section. Lists are\nconstructed with square brackets, separating items with commas: ``[a,\nb, c]``. Tuples are constructed by the comma operator (not within\nsquare brackets), with or without enclosing parentheses, but an empty\ntuple must have the enclosing parentheses, such as ``a, b, c`` or\n``()``. A single item tuple must have a trailing comma, such as\n``(d,)``.\n\nBytearray objects are created with the built-in function\n``bytearray()``.\n\nBuffer objects are not directly supported by Python syntax, but can be\ncreated by calling the built-in function ``buffer()``. They don\'t\nsupport concatenation or repetition.\n\nObjects of type xrange are similar to buffers in that there is no\nspecific syntax to create them, but they are created using the\n``xrange()`` function. They don\'t support slicing, concatenation or\nrepetition, and using ``in``, ``not in``, ``min()`` or ``max()`` on\nthem is inefficient.\n\nMost sequence types support the following operations. The ``in`` and\n``not in`` operations have the same priorities as the comparison\noperations. The ``+`` and ``*`` operations have the same priority as\nthe corresponding numeric operations. [3] Additional methods are\nprovided for *Mutable Sequence Types*.\n\nThis table lists the sequence operations sorted in ascending priority\n(operations in the same box have the same priority). In the table,\n*s* and *t* are sequences of the same type; *n*, *i* and *j* are\nintegers:\n\n+--------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+====================+==================================+============+\n| ``x in s`` | ``True`` if an item of *s* is | (1) |\n| | equal to *x*, else ``False`` | |\n+--------------------+----------------------------------+------------+\n| ``x not in s`` | ``False`` if an item of *s* is | (1) |\n| | equal to *x*, else ``True`` | |\n+--------------------+----------------------------------+------------+\n| ``s + t`` | the concatenation of *s* and *t* | (6) |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s`` | *n* shallow copies of *s* | (2) |\n| | concatenated | |\n+--------------------+----------------------------------+------------+\n| ``s[i]`` | *i*th item of *s*, origin 0 | (3) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]`` | slice of *s* from *i* to *j* | (3)(4) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]`` | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+--------------------+----------------------------------+------------+\n| ``len(s)`` | length of *s* | |\n+--------------------+----------------------------------+------------+\n| ``min(s)`` | smallest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``max(s)`` | largest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``s.index(i)`` | index of the first occurence of | |\n| | *i* in *s* | |\n+--------------------+----------------------------------+------------+\n| ``s.count(i)`` | total number of occurences of | |\n| | *i* in *s* | |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular
