Searched defs:See (Results 1 - 23 of 23) sorted by relevance

/external/libunwind/doc/
H A Dunw_destroy_addr_space.tex27 \section{See Also}
H A Dlibunwind-setjmp.tex72 \section{See Also}
H A Dunw_backtrace.tex41 \section{See Also}
H A Dlibunwind-ia64.tex204 \section{See Also}
H A Dunw_flush_cache.tex44 \section{See Also}
H A Dunw_get_accessors.tex41 \section{See Also}
H A Dunw_get_fpreg.tex34 floating-point registers. See \Func{unw\_get\_fpreg}(3) for a way to
60 \section{See Also}
H A Dunw_get_proc_info.tex109 \section{See Also}
H A Dunw_get_proc_info_by_ip.tex75 \section{See Also}
H A Dunw_get_proc_name.tex69 \section{See Also}
H A Dunw_get_reg.tex34 registers whose values fit in a single word. See
61 \section{See Also}
H A Dunw_getcontext.tex50 \section{See Also}
H A Dunw_is_fpreg.tex36 \section{See Also}
H A Dunw_is_signal_frame.tex51 \section{See Also}
H A Dunw_regname.tex35 \section{See Also}
H A Dunw_set_caching_policy.tex66 \section{See Also}
H A Dunw_set_fpreg.tex34 floating-point registers. See \Func{unw\_set\_reg}(3) for a way to
62 \section{See Also}
H A Dunw_set_reg.tex34 registers whose values fit in a single word. See
63 \section{See Also}
H A Dunw_step.tex55 \section{See Also}
/external/lzma/C/
H A DPpmd7.h58 CPpmd_See DummySee, See[25][16]; member in struct:__anon14158
/external/iproute2/doc/
H A Dip-cref.tex883 \paragraph{See also:} Appendix~\ref{PROXY-NEIGH}, p.\pageref{PROXY-NEIGH}
1238 is used. See sec.\ref{IP-RULE}, p.\pageref{IP-RULE}.
1671 in an error. See attribute \verb|error| below (p.\pageref{IP-ROUTE-GET-error}).
1740 \verb|ip route save| is that of \verb|rtnetlink|. See
2265 \verb|ip rule save| is that of \verb|rtnetlink|. See
2330 with \verb|ip maddr add|. See the following subsection.
2471 \paragraph{See also:} A more informal discussion of tunneling
/external/speex/libspeex/
H A Dmdf.c696 spx_word32_t Syy,See,Sxx,Sdd, Sff; local
878 See = 0;
890 See += mdf_inner_prod(st->e+chan*N, st->e+chan*N, st->frame_size);
895 Sff = See;
902 st->Davg1 = ADD32(MULT16_32_Q15(QCONST16(.6f,15),st->Davg1), MULT16_32_Q15(QCONST16(.4f,15),SUB32(Sff,See)));
903 st->Davg2 = ADD32(MULT16_32_Q15(QCONST16(.85f,15),st->Davg2), MULT16_32_Q15(QCONST16(.15f,15),SUB32(Sff,See)));
908 st->Davg1 = .6*st->Davg1 + .4*(Sff-See);
909 st->Davg2 = .85*st->Davg2 + .15*(Sff-See);
917 if (FLOAT_GT(FLOAT_MUL32U(SUB32(Sff,See),ABS32(SUB32(Sff,See))), FLOAT_MUL32
[all...]
/external/python/cpython2/Lib/pydoc_data/
H A Dtopics.py4 '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\n object must be an iterable with the same number of items as there\n are targets in the target list, and the items are assigned, from\n left to right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n * If the name does not occur in a "global" 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\n square brackets: The object must be an iterable with the same number\n of 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 always\n set as an instance attribute, creating it if necessary. Thus, the\n two occurrences of "a.x" do not necessarily refer to the same\n attribute: if the RHS expression refers to a class attribute, the\n LHS creates a new instance attribute as the target of the\n assignment:\n\n class Cls:\n x = 3 # class variable\n inst = Cls()\n inst.x = inst.x + 1 # writes inst.x as 4 leaving Cls.x as 3\n\n This description does not necessarily apply to descriptor\n attributes, such as properties created with "property()".\n\n* If the target is a subscription: The primary expression in the\n reference is evaluated. It should yield either a mutable sequence\n object (such as a list) or a mapping object (such as a dictionary).\n Next, the subscript expression is evaluated.\n\n If the primary is a mutable sequence object (such as a list), the\n subscript must yield a plain integer. If it is negative, the\n sequence\'s length is added to it. The resulting value must be a\n nonnegative integer less than the sequence\'s length, and the\n sequence is asked to assign the assigned object to its item with\n that index. If the index is out of range, "IndexError" is raised\n (assignment to a subscripted sequence cannot add new items to a\n list).\n\n If the primary is a mapping object (such as a dictionary), the\n subscript must have a type compatible with the mapping\'s key type,\n and the mapping is then asked to create a key/datum pair which maps\n the subscript to the assigned object. This can either replace an\n existing key/value pair with the same key value, or insert a new\n key/value pair (if no key with the same value existed).\n\n* If the target is a slicing: The primary expression in the\n reference is evaluated. It should yield a mutable sequence object\n (such as a list). The assigned object should be a sequence object\n of the same type. Next, the lower and upper bound expressions are\n evaluated, insofar they are present; defaults are zero and the\n sequence\'s length. The bounds should evaluate to (small) integers.\n If either bound is negative, the sequence\'s length is added to it.\n The resulting bounds are clipped to lie between zero and the\n sequence\'s length, inclusive. Finally, the sequence object is asked\n to replace the slice with the items of the assigned sequence. The\n length of the slice may be different from the length of the assigned\n sequence, thus changing the length of the target sequence, if the\n object allows it.\n\n**CPython implementation detail:** In the current implementation, the\nsyntax for targets is taken to be the same as for expressions, and\ninvalid syntax is rejected during the code generation phase, causing\nless detailed error messages.\n\nWARNING: Although the definition of assignment implies that overlaps\nbetween the left-hand side and the right-hand side are \'safe\' (for\nexample "a, b = b, a" swaps two variables), overlaps *within* the\ncollection of assigned-to variables are not safe! For instance, the\nfollowing program prints "[0, 2]":\n\n x = [0, 1]\n i = 0\n i, x[i] = 1, 2\n print x\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n augtarget ::= identifier | attributeref | subscription | slicing\n augop ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section Primaries for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like "x += 1" can be rewritten as\n"x = x + 1" to achieve a similar, but not exactly equal effect. In the\naugmented version, "x" is only evaluated once. Also, when possible,\nthe actual operation is performed *in-place*, meaning that rather than\ncreating a new object and assigning that to the target, the old object\nis 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',
5 'atom-identifiers': u'\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name. See section Identifiers\nand keywords for lexical definition and section Naming and binding for\ndocumentation 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, with leading underscores removed and a single underscore\ninserted, in front of the name. For example, the identifier "__spam"\noccurring in a class named "Ham" will be transformed to "_Ham__spam".\nThis transformation is independent of the syntactical context in which\nthe identifier is used. If the transformed name is extremely long\n(longer than 255 characters), implementation defined truncation may\nhappen. If the class name consists only of underscores, no\ntransformation is done.\n',
6 '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",
7 '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") for\nclass 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. This\n method should return the (computed) attribute value or raise an\n "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 for\n efficiency reasons and because otherwise "__getattr__()" would have\n no way to access other attributes of the instance. Note that at\n least for instance variables, you can fake total control by not\n 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 cause\n a recursive call to itself. Instead, it should insert the value in\n the dictionary of instance attributes, e.g., "self.__dict__[name] =\n value". For new-style classes, rather than accessing the instance\n dictionary, it should call the base class method with the same\n name, for example, "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 "__getattr__()",\n the latter will not be called unless "__getattribute__()" either\n calls it explicitly or raises an "AttributeError". This method\n should return the (computed) attribute value or raise an\n "AttributeError" exception. In order to avoid infinite recursion in\n this method, its implementation should always call the base class\n method with the same name to access any attributes it needs, for\n example, "object.__getattribute__(self, name)".\n\n Note: This method may still be bypassed when looking up special\n methods as the result of implicit invocation via language syntax\n or 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 an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' "__dict__".\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or "None" when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an "AttributeError"\n exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n====================\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: "__get__()", "__set__()", and\n"__delete__()". If any of those methods are defined for an object, it\nis said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, "a.x" has a\nlookup chain starting with "a.__dict__[\'x\']", then\n"type(a).__dict__[\'x\']", and continuing through the base classes of\n"type(a)" excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called. Note that descriptors are only invoked for new\nstyle objects or classes (ones that subclass "object()" or "type()").\n\nThe starting point for descriptor invocation is a binding, "a.x". How\nthe arguments are assembled depends on "a":\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: "x.__get__(a)".\n\nInstance Binding\n If binding to a new-style object instance, "a.x" is transformed\n into the call: "type(a).__dict__[\'x\'].__get__(a, type(a))".\n\nClass Binding\n If binding to a new-style class, "A.x" is transformed into the\n call: "A.__dict__[\'x\'].__get__(None, A)".\n\nSuper Binding\n If "a" is an instance of "super", then the binding "super(B,\n obj).m()" searches "obj.__class__.__mro__" for the base class "A"\n immediately preceding "B" and then invokes the descriptor with the\n call: "A.__dict__[\'m\'].__get__(obj, obj.__class__)".\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of "__get__()", "__set__()" and "__delete__()". If it\ndoes not define "__get__()", then accessing the attribute will return\nthe descriptor object itself unless there is a value in the object\'s\ninstance dictionary. If the descriptor defines "__set__()" and/or\n"__delete__()", it is a data descriptor; if it defines neither, it is\na non-data descriptor. Normally, data descriptors define both\n"__get__()" and "__set__()", while non-data descriptors have just the\n"__get__()" method. Data descriptors with "__set__()" and "__get__()"\ndefined always override a redefinition in an instance dictionary. In\ncontrast, non-data descriptors can be overridden by instances.\n\nPython methods (including "staticmethod()" and "classmethod()") are\nimplemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe "property()" function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n=========\n\nBy default, instances of both old and new-style classes have a\ndictionary for attribute storage. This wastes space for objects\nhaving very few instance variables. The space consumption can become\nacute when creating large numbers of instances.\n\nThe default can be overridden by defining *__slots__* in a new-style\nclass definition. The *__slots__* declaration takes a sequence of\ninstance variables and reserves just enough space in each instance to\nhold a value for each variable. Space is saved because *__dict__* is\nnot created for each instance.\n\n__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n new-style class, *__slots__* reserves space for the declared\n variables and prevents the automatic creation of *__dict__* and\n *__weakref__* for each instance.\n\n New in version 2.2.\n\nNotes on using *__slots__*\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises "AttributeError". If\n dynamic assignment of new variables is desired, then add\n "\'__dict__\'" to the sequence of strings in the *__slots__*\n declaration.\n\n Changed in version 2.3: Previously, adding "\'__dict__\'" to the\n *__slots__* declaration would not enable the assignment of new\n attributes not specifically listed in the sequence of instance\n variable names.\n\n* Without a *__weakref__* variable for each instance, classes\n defining *__slots__* do not support weak references to its\n instances. If weak reference support is needed, then add\n "\'__weakref__\'" to the sequence of strings in the *__slots__*\n declaration.\n\n Changed in version 2.3: Previously, adding "\'__weakref__\'" to the\n *__slots__* declaration would not enable support for weak\n references.\n\n* *__slots__* are implemented at the class level by creating\n descriptors (Implementing Descriptors) for each variable name. As a\n result, class attributes cannot be used to set default values for\n instance variables defined by *__slots__*; otherwise, the class\n attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n where it is defined. As a result, subclasses will have a *__dict__*\n unless they also define *__slots__* (which must only contain names\n of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the\n instance variable defined by the base class slot is inaccessible\n (except by retrieving its descriptor directly from the base class).\n This renders the meaning of the program undefined. In the future, a\n check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n "variable-length" built-in types such as "long", "str" and "tuple".\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings\n may also be used; however, in the future, special meaning may be\n assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n *__slots__*.\n\n Changed in version 2.6: Previously, *__class__* assignment raised an\n error if either new or old class had *__slots__*.\n',
9 '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 the\naugmented version, "x" is only evaluated once. Also, when possible,\nthe actual operation is performed *in-place*, meaning that rather than\ncreating a new object and assigning that to the target, the old object\nis 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',
12 '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',
17 'booleans': u'\nBoolean operations\n******************\n\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 change\nthis.)\n\nThe operator "not" yields "True" if its argument is false, "False"\notherwise.\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 value\nis returned; otherwise, *y* is evaluated and the resulting value is\nreturned.\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 invent a\nvalue anyway, it does not bother to return a value of the same type as\nits argument, so e.g., "not \'foo\'" yields "False", not "\'\'".)\n',
23 '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 control\nflow constructs. "try" specifies exception handlers and/or cleanup\ncode for a group of statements. Function and class definitions are\nalso 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 a\n"DEDENT". Also note that optional continuation clauses always begin\nwith 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 executed\nand the loop terminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and goes back\nto testing the expression.\n\n\nThe "for" statement\n===================\n\nThe "for" statement is used to iterate over the elements of a sequence\n(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" statement\nexecuted in the first suite skips the rest of the suite and continues\nwith the next item, or with the "else" clause if there was no next\nitem.\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\n loop (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe "try" statement\n===================\n\nThe "try" statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression [("as" | ",") identifier]] ":" 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" had to be\nnested in "try"..."finally".\n\nThe "except" clause(s) specify one or more exception handlers. When no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject, or a tuple containing an item compatible with the exception.\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 raised\nthe 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 are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception, it is re-raised at the end of the\n"finally" clause. If the "finally" clause raises another exception or\nexecutes a "return" or "break" statement, the saved exception is\ndiscarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\n\nAdditional information on exceptions can be found in section\nExceptions, and information on using the "raise" statement to generate\nexceptions may be found in section The raise statement.\n\n\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 "try"..."except"..."finally"\nusage patterns to be encapsulated for convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the "with" statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the "with_item")\n is evaluated to obtain a context manager.\n\n2. The context manager\'s "__exit__()" is loaded for later use.\n\n3. The context manager\'s "__enter__()" method is invoked.\n\n4. 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 be\n 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 ste
27 '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 an\\n 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 after the instance has been created (by "__new__()"), but\\n before it is returned to the caller. 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, if\\n any, must explicitly call it to ensure proper initialization of the\\n base class part of the instance; for example:\\n "BaseClass.__init__(self, [args...])".\\n\\n Because "__new__()" and "__init__()" work together in constructing\\n objects ("__new__()" to create it, and "__init__()" to customise\\n it), no non-"None" value may be returned by "__init__()"; doing so\\n will cause a "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, the\\n derived class\\'s "__del__()" method, if any, must explicitly call it\\n to ensure proper deletion of the base class part of the instance.\\n Note that it is possible (though not recommended!) for the\\n "__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 is\\n only called when "x"\\'s reference count reaches zero. Some common\\n situations that may prevent the reference count of an object from\\n going to zero include: circular references between objects (e.g.,\\n a doubly-linked list or a tree data structure with parent and\\n child pointers); a reference to the object on the stack frame of\\n a function that caught an exception (the traceback stored in\\n "sys.exc_traceback" keeps the stack frame alive); or a reference\\n to the object on the stack frame that raised an unhandled\\n 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 references\\n which are garbage are detected when the option cycle detector is\\n enabled (it\\'s on by default), but can only be cleaned up if there\\n are no Python-level "__del__()" methods involved. Refer to the\\n documentation for the "gc" module for more information about how\\n "__del__()" methods are handled by the cycle detector,\\n particularly the description of the "garbage" value.\\n\\n Warning: Due to the precarious circumstances under which\\n "__del__()" methods are invoked, exceptions that occur during\\n their execution are ignored, and a warning is printed to\\n "sys.stderr" instead. Also, when "__del__()" is invoked in\\n response to a module being deleted (e.g., when execution of the\\n program is done), other globals referenced by the "__del__()"\\n method may already have been deleted or in the process of being\\n torn down (e.g. the import machinery shutting down). For this\\n reason, "__del__()" methods should do the absolute minimum needed\\n to maintain external invariants. Starting with version 1.5,\\n Python guarantees that globals whose name begins with a single\\n underscore are deleted from their module before other globals are\\n deleted; if no other references to such globals exist, this may\\n help in assuring that imported modules are still available at the\\n time when the "__del__()" method is called.\\n\\n See also the "-R" command-line option.\\n\\nobject.__repr__(self)\\n\\n Called by the "repr()" built-in function and by string conversions\\n (reverse quotes) to compute the "official" string representation of\\n an object. If at all possible, this should look like a valid\\n Python expression that could be used to recreate an object with the\\n same value (given an appropriate environment). If this is not\\n possible, a string of the form "<...some useful description...>"\\n should be returned. The return value must be a string object. If a\\n class defines "__repr__()" but not "__str__()", then "__repr__()"\\n is also used when an "informal" string representation of instances\\n of that class is required.\\n\\n This is typically used for debugging, so it is important that the\\n representation is information-rich and unambiguous.\\n\\nobject.__str__(self)\\n\\n Called by the "str()" built-in function and by the "print"\\n statement to compute the "informal" string representation of an\\n object. This differs from "__repr__()" in that it does not have to\\n be a valid Python expression: a more convenient or concise\\n representation may be used instead. The return value must be a\\n string object.\\n\\nobject.__lt__(self, other)\\nobject.__le__(self, other)\\nobject.__eq__(self, other)\\nobject.__ne__(self, other)\\nobject.__gt__(self, other)\\nobject.__ge__(self, other)\\n\\n New in version 2.1.\\n\\n These are the so-called "rich comparison" methods, and are called\\n for comparison operators in preference to "__cmp__()" below. The\\n correspondence between operator symbols and method names is as\\n follows: "x<y" calls "x.__lt__(y)", "x<=y" calls "x.__le__(y)",\\n "x==y" calls "x.__eq__(y)", "x!=y" and "x<>y" call "x.__ne__(y)",\\n "x>y" calls "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".\\n\\n A rich comparison method may return the singleton "NotImplemented"\\n if it does not implement the operation for a given pair of\\n arguments. By convention, "False" and "True" are returned for a\\n successful comparison. However, these methods can return any value,\\n so if the comparison operator is used in a Boolean context (e.g.,\\n in the condition of an "if" statement), Python will call "bool()"\\n on the value to determine if the result is true or false.\\n\\n There are no implied relationships among the comparison operators.\\n The truth of "x==y" does not imply that "x!=y" is false.\\n Accordingly, when defining "__eq__()", one should also define\\n "__ne__()" so that the operators will behave as expected. See the\\n paragraph on "__hash__()" for some important notes on creating\\n *hashable* objects which support custom comparison operations and\\n are usable as dictionary keys.\\n\\n There are no swapped-argument versions of these methods (to be used\\n when the left argument does not support the operation but the right\\n argument does); rather, "__lt__()" and "__gt__()" are each other\\'s\\n reflection, "__le__()" and "__ge__()" are each other\\'s reflection,\\n and "__eq__()" and "__ne__()" are their own reflection.\\n\\n Arguments to rich comparison methods are never coerced.\\n\\n To automatically generate ordering operations from a single root\\n operation, see "functools.total_ordering()".\\n\\nobject.__cmp__(self, other)\\n\\n Called by comparison operations if rich comparison (see above) is\\n not defined. Should return a negative integer if "self < other",\\n zero if "self == other", a positive integer if "self > other". If\\n no "__cmp__()", "__eq__()" or "__ne__()" operation is defined,\\n class instances are compared by object identity ("address"). See\\n also the description of "__hash__()" for some important notes on\\n creating *hashable* objects which support custom comparison\\n operations and are usable as dictionary keys. (Note: the\\n restriction that exceptions are not propagated by "__cmp__()" has\\n been removed since Python 1.5.)\\n\\nobject.__rcmp__(self, other)\\n\\n Changed in version 2.1: No longer supported.\\n\\nobject.__hash__(self)\\n\\n Called by built-in function "hash()" and for operations on members\\n of hashed collections including "set", "frozenset", and "dict".\\n "__hash__()" should return an integer. The only required property\\n is that objects which compare equal have the same hash value; it is\\n advised to somehow mix together (e.g. using exclusive or) the hash\\n values for the components of the object that also play a part in\\n comparison of objects.\\n\\n If a class does not define a "__cmp__()" or "__eq__()" method it\\n should not define a "__hash__()" operation either; if it defines\\n "__cmp__()" or "__eq__()" but not "__hash__()", its instances will\\n not be usable in hashed collections. If a class defines mutable\\n objects and implements a "__cmp__()" or "__eq__()" method, it\\n should not implement "__hash__()", since hashable collection\\n implementations require that an object\\'s hash value is immutable\\n (if the object\\'s hash value changes, it will be in the wrong hash\\n bucket).\\n\\n User-defined classes have "__cmp__()" and "__hash__()" methods by\\n default; with them, all objects compare unequal (except with\\n themselves) and "x.__hash__()" returns a result derived from\\n "id(x)".\\n\\n Classes which inherit a "__hash__()" method from a parent class but\\n change the meaning of "__cmp__()" or "__eq__()" such that the hash\\n value returned is no longer appropriate (e.g. by switching to a\\n value-based concept of equality instead of the default identity\\n based equality) can explicitly flag themselves as being unhashable\\n by setting "__hash__ = None" in the class definition. Doing so\\n means that not only will instances of the class raise an\\n appropriate "TypeError" when a program attempts to retrieve their\\n hash value, but they will also be correctly identified as\\n unhashable when checking "isinstance(obj, collections.Hashable)"\\n (unlike classes which define their own "__hash__()" to explicitly\\n raise "TypeError").\\n\\n Changed in version 2.5: "__hash__()" may now also return a long\\n integer object; the 32-bit integer is then derived from the hash of\\n that object.\\n\\n Changed in version 2.6: "__hash__" may now be set to "None" to\\n explicitly flag instances of a class as unhashable.\\n\\nobject.__nonzero__(self)\\n\\n Called to implement truth value testing and the built-in operation\\n "bool()"; should return "False" or "True", or their integer\\n equivalents "0" or "1". When this method is not defined,\\n "__len__()" is called, if it is defined, and the object is\\n considered true if its result is nonzero. If a class defines\\n neither "__len__()" nor "__nonzero__()", all its instances are\\n considered true.\\n\\nobject.__unicode__(self)\\n\\n Called to implement "unicode()" built-in; should return a Unicode\\n object. When this method is not defined, string conversion is\\n attempted, and the result of string conversion is converted to\\n Unicode using the system default encoding.\\n', namespace
43 '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 recognized\\nby the compiler as a name for the built-in object "None". Although it\\nis not a keyword, you cannot assign a different object to it.\\n\\nChanged in version 2.5: Using "as" and "with" as identifiers triggers\\na warning. To use them as keywords, enable the "with_statement"\\nfuture feature .\\n\\nChanged in version 2.6: "as" and "with" are full keywords.\\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 the\\n last evaluation; it is stored in the "__builtin__" module. When\\n not in interactive mode, "_" has no special meaning and is not\\n defined. See section The import statement.\\n\\n Note: The name "_" is often used in conjunction with\\n internationalization; refer to the documentation for the\\n "gettext" module for more information on this convention.\\n\\n"__*__"\\n System-defined names. These names are defined by the interpreter\\n and its implementation (including the standard library). Current\\n system names are discussed in the Special method names section and\\n elsewhere. More will likely be defined in future versions of\\n Python. *Any* use of "__*__" names, in any context, that does not\\n follow explicitly documented use, is subject to breakage without\\n warning.\\n\\n"__*"\\n Class-private names. Names in this category, when used within the\\n context of a class definition, are re-written to use a mangled form\\n to help avoid name clashes between "private" attributes of base and\\n derived classes. See section Identifiers (Names).\\n', namespace
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