Lines Matching refs:nSet
34 '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 Unicode string, a *Latin-1*\nencoded string, an open file object, a code object, or a tuple. If it\nis a string, the string is parsed as a suite of Python statements\nwhich is then executed (unless a syntax error occurs). [1] If it is an\nopen file, the file is parsed until EOF and executed. If it is a code\nobject, it is simply executed. For the interpretation of a tuple, see\nbelow. In all cases, the code that\'s executed is expected to be valid\nas file input (see section File input). Be aware that the "return"\nand "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. Remember that at module\nlevel, globals and locals are the same dictionary. If two separate\nobjects are given as *globals* and *locals*, the code will be executed\nas if it were embedded in a class definition.\n\nThe first expression may also be a tuple of length 2 or 3. In this\ncase, the optional parts must be omitted. The form "exec(expr,\nglobals)" is equivalent to "exec expr in globals", while the form\n"exec(expr, globals, locals)" is equivalent to "exec expr in globals,\nlocals". The tuple form of "exec" provides compatibility with Python\n3, where "exec" is a function rather than a statement.\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 "__builtin__"\nunder the key "__builtins__" (!).\n\n**Programmer\'s hints:** dynamic evaluation of expressions is supported\nby the built-in function "eval()". The built-in functions "globals()"\nand "locals()" return the current global and local dictionary,\nrespectively, which may be useful to pass around for use by "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 newlines* mode to convert Windows or Mac-style\n newlines.\n',
35 nset to a user-created dictionary to create a weak form of restricted\nexecution.\n\n**CPython implementation detail:** Users should not touch\n"__builtins__"; it is strictly an implementation detail. Users\nwanting to override values in the builtins namespace should "import"\nthe "__builtin__" (no \'s\') module and modify its attributes\nappropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n"__main__".\n\nThe "global" statement has the same scope as a name binding operation\nin the same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\nInteraction with dynamic features\n---------------------------------\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- "import *" --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a "SyntaxError".\n\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 namespace\nfor the "exec". (In other words, "exec obj" would be illegal, but\n"exec obj in ns" would be legal.)\n\nThe "eval()", "execfile()", and "input()" functions and the "exec"\nstatement do not have access to the full environment for resolving\nnames. Names may be resolved in the local and global namespaces of\nthe caller. Free variables are not resolved in the nearest enclosing\nnamespace, but in the global namespace. [1] The "exec" statement and\nthe "eval()" and "execfile()" functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n\n\nExceptions\n==========\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the "raise" statement. Exception\nhandlers are specified with the "try" ... "except" statement. The\n"finally" clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n"SystemExit".\n\nExceptions are identified by class instances. The "except" clause is\nselected depending on the class of the instance: it must reference the\nclass of the instance or a base class thereof. The instance can be\nreceived by the handler and can carry additional information about the\nexceptional 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\n these operations is not available at the time the module is\n compiled.\n',
51 nset to a user-created dictionary to create a weak form of restricted\nexecution.\n\n**CPython implementation detail:** Users should not touch\n"__builtins__"; it is strictly an implementation detail. Users\nwanting to override values in the builtins namespace should "import"\nthe "__builtin__" (no \'s\') module and modify its attributes\nappropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n"__main__".\n\nThe "global" statement has the same scope as a name binding operation\nin the same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\nInteraction with dynamic features\n=================================\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- "import *" --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a "SyntaxError".\n\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 namespace\nfor the "exec". (In other words, "exec obj" would be illegal, but\n"exec obj in ns" would be legal.)\n\nThe "eval()", "execfile()", and "input()" functions and the "exec"\nstatement do not have access to the full environment for resolving\nnames. Names may be resolved in the local and global namespaces of\nthe caller. Free variables are not resolved in the nearest enclosing\nnamespace, but in the global namespace. [1] The "exec" statement and\nthe "eval()" and "execfile()" functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n',
71 '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". It\n is used to signify the absence of a value in many situations, e.g.,\n 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 "..." syntax\n 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\n only 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 and the least surprises when\n switching between the plain and long integer domains. Any\n operation, if it yields a result in the plain integer domain,\n will yield the same result in the long integer domain or when\n using mixed operands. The switch between domains is transparent\n to the programmer.\n\n "numbers.Real" ("float")\n These represent machine-level double precision floating point\n numbers. You are at the mercy of the underlying machine\n architecture (and C or Java implementation) for the accepted\n range and handling of overflow. Python does not support single-\n precision floating point numbers; the savings in processor and\n memory usage that are usually the reason for using these are\n dwarfed by the overhead of using objects in Python, so there is\n no reason to complicate the language with two kinds of floating\n point numbers.\n\n "numbers.Complex"\n These represent complex numbers as a pair of machine-level\n double precision floating point numbers. The same caveats apply\n as for floating point numbers. The real and imaginary parts of a\n complex number "z" can be retrieved through the read-only\n attributes "z.real" and "z.imag".\n\nSequences\n These represent finite ordered sets indexed by non-negative\n numbers. The built-in function "len()" returns the number of items\n of a sequence. When the length of a sequence is *n*, the index set\n contains the numbers 0, 1, ..., *n*-1. Item *i* of sequence *a* is\n selected by "a[i]".\n\n Sequences also support slicing: "a[i:j]" selects all items with\n index *k* such that *i* "<=" *k* "<" *j*. When used as an\n expression, a slice is a sequence of the same type. This implies\n that the index set is renumbered so that it starts at 0.\n\n Some sequences also support "extended slicing" with a third "step"\n parameter: "a[i:j:k]" selects all items of *a* with index *x* where\n "x = i + n*k", *n* ">=" "0" and *i* "<=" *x* "<" *j*.\n\n Sequences are distinguished according to their mutability:\n\n Immutable sequences\n An object of an immutable sequence type cannot change once it is\n created. (If the object contains references to other objects,\n these other objects may be mutable and may be changed; however,\n the collection of objects directly referenced by an immutable\n object cannot change.)\n\n The following types are immutable sequences:\n\n Strings\n The items of a string are characters. There is no separate\n character type; a character is represented by a string of one\n item. Characters represent (at least) 8-bit bytes. The\n built-in functions "chr()" and "ord()" convert between\n characters and nonnegative integers representing the byte\n values. Bytes with the values 0--127 usually represent the\n corresponding ASCII values, but the interpretation of values\n is up to the program. The string data type is also used to\n represent arrays of bytes, e.g., to hold data read from a\n file.\n\n (On systems whose native character set is not ASCII, strings\n may use EBCDIC in their internal representation, provided the\n functions "chr()" and "ord()" implement a mapping between\n ASCII and EBCDIC, and string comparison preserves the ASCII\n order. Or perhaps someone can propose a better rule?)\n\n Unicode\n The items of a Unicode object are Unicode code units. A\n Unicode code unit is represented by a Unicode object of one\n item and can hold either a 16-bit or 32-bit value\n representing a Unicode ordinal (the maximum value for the\n ordinal is given in "sys.maxunicode", and depends on how\n Python is configured at compile time). Surrogate pairs may\n be present in the Unicode object, and will be reported as two\n separate items. The built-in functions "unichr()" and\n "ord()" convert between code units and nonnegative integers\n representing the Unicode ordinals as defined in the Unicode\n Standard 3.0. Conversion from and to other encodings are\n possible through the Unicode method "encode()" and the built-\n in function "unicode()".\n\n Tuples\n The items of a tuple are arbitrary Python objects. Tuples of\n two or more items are formed by comma-separated lists of\n expressions. A tuple of one item (a \'singleton\') can be\n formed by affixing a comma to an expression (an expression by\n itself does not create a tuple, since parentheses must be\n usable for grouping of expressions). An empty tuple can be\n formed by an empty pair of parentheses.\n\n Mutable sequences\n Mutable sequences can be changed after they are created. The\n subscription and slicing notations can be used as the target of\n assignment and "del" (delete) statements.\n\n There are currently two intrinsic mutable sequence types:\n\n Lists\n The items of a list are arbitrary Python objects. Lists are\n formed by placing a comma-separated list of expressions in\n square brackets. (Note that there are no special cases needed\n to form lists of length 0 or 1.)\n\n Byte Arrays\n A bytearray object is a mutable array. They are created by\n the built-in "bytearray()" constructor. Aside from being\n mutable (and hence unhashable), byte arrays otherwise provide\n the same interface and functionality as immutable bytes\n objects.\n\n The extension module "array" provides an additional example of a\n mutable sequence type.\n\nSet
