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3  'assignment': u'\nAssignment statements\n*********************\n\nAssignment statements are used to (re)bind names to values and to\nmodify attributes or items of mutable objects:\n\n   assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)\n   target_list     ::= target ("," target)* [","]\n   target          ::= identifier\n              | "(" target_list ")"\n              | "[" target_list "]"\n              | attributeref\n              | subscription\n              | slicing\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable.  The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list is recursively defined as\nfollows.\n\n* If the target list is a single target: The object is assigned to\n  that target.\n\n* If the target list is a comma-separated list of targets: The object\n  must be an iterable with the same number of items as there are\n  targets in the target list, and the items are assigned, from left to\n  right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n  * If the name does not occur in a ``global`` statement in the\n    current code block: the name is bound to the object in the current\n    local namespace.\n\n  * Otherwise: the name is bound to the object in the current global\n    namespace.\n\n  The name is rebound if it was already bound.  This may cause the\n  reference count for the object previously bound to the name to reach\n  zero, causing the object to be deallocated and its destructor (if it\n  has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in square\n  brackets: The object must be an iterable with the same number of\n  items as there are targets in the target list, and its items are\n  assigned, from left to right, to the corresponding targets.\n\n* If the target is an attribute reference: The primary expression in\n  the reference is evaluated.  It should yield an object with\n  assignable attributes; if this is not the case, ``TypeError`` is\n  raised.  That object is then asked to assign the assigned object to\n  the given attribute; if it cannot perform the assignment, it raises\n  an exception (usually but not necessarily ``AttributeError``).\n\n  Note: If the object is a class instance and the attribute reference\n  occurs on both sides of the assignment operator, the RHS expression,\n  ``a.x`` can access either an instance attribute or (if no instance\n  attribute exists) a class attribute.  The LHS target ``a.x`` is\n  always set as an instance attribute, creating it if necessary.\n  Thus, the two occurrences of ``a.x`` do not necessarily refer to the\n  same attribute: if the RHS expression refers to a class attribute,\n  the LHS creates a new instance attribute as the target of the\n  assignment:\n\n     class Cls:\n         x = 3             # class variable\n     inst = Cls()\n     inst.x = inst.x + 1   # writes inst.x as 4 leaving Cls.x as 3\n\n  This description does not necessarily apply to descriptor\n  attributes, such as properties 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 reference\n  is evaluated.  It should yield a mutable sequence object (such as a\n  list).  The assigned object should be a sequence object of the same\n  type.  Next, the lower and upper bound expressions are evaluated,\n  insofar they are present; defaults are zero and the sequence\'s\n  length.  The bounds should evaluate to (small) integers.  If either\n  bound is negative, the sequence\'s length is added to it. The\n  resulting bounds are clipped to lie between zero and the sequence\'s\n  length, inclusive.  Finally, the sequence object is asked to replace\n  the slice with the items of the assigned sequence.  The length of\n  the slice may be different from the length of the assigned sequence,\n  thus changing the length of the target sequence, if the object\n  allows it.\n\n**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\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',

6 'attribute-access': u'\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control in new-style classes.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should not simply execute ``self.name = value`` --- this would\n cause a recursive call to itself. Instead, it should insert the\n value in the dictionary of instance attributes, e.g.,\n ``self.__dict__[name] = value``. For new-style classes, rather\n than accessing the instance dictionary, it should call the base\n class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignmentassignment 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 defining\n *__slots__* do not support weak references to its instances. If weak\n reference support is needed, then add ``\'__weakref__\'`` to the\n sequence of strings in the *__slots__* 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\n a 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 instance\n variable defined by the base class slot is inaccessible (except by\n retrieving its descriptor directly from the base class). This\n 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\n ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n 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',
8 'augassign': u'\nAugmented assignment statements\n*******************************\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n augtarget ::= identifier | attributeref | subscription | slicing\n augop ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like ``x += 1`` can be rewritten as\n``x = x + 1`` to achieve a similar, but not exactly equal effect. In\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',
19 assignment rules after all other\nparameter processing is done.\n\nA call always returns some value, possibly ``None``, unless it raises\nan exception. How this value is computed depends on the type of the\ncallable object.\n\nIf it is---\n\na user-defined function:\n The code block for the function is executed, passing it the\n argument list. The first thing the code block will do is bind the\n formal parameters to the arguments; this is described in section\n *Function definitions*. When the code block executes a ``return``\n statement, this specifies the return value of the function call.\n\na built-in function or method:\n The result is up to the interpreter; see *Built-in Functions* for\n the descriptions of built-in functions and methods.\n\na class object:\n A new instance of that class is returned.\n\na class instance method:\n The corresponding user-defined function is called, with an argument\n list that is one longer than the argument list of the call: the\n instance becomes the first argument.\n\na class instance:\n The class must define a ``__call__()`` method; the effect is then\n the same as if that method was called.\n',
23 assignment
29 'del': u'\nThe ``del`` statement\n*********************\n\n del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather that spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block. If the name is unbound, a\n``NameError`` exception will be raised.\n\nIt is illegal to delete a name from the local namespace if it occurs\nas a free variable in a nested block.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n',
35 'execmodel': u'\nExecution model\n***************\n\n\nNaming and binding\n==================\n\n*Names* refer to objects. Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block. A script\nfile (a file given as standard input to the interpreter or specified\non the interpreter command line the first argument) is a code block.\nA script command (a command specified on the interpreter command line\nwith the \'**-c**\' option) is a code block. The file read by the\nbuilt-in function ``execfile()`` is a code block. The string argument\npassed to the built-in function ``eval()`` and to the ``exec``\nstatement is a code block. The expression read and evaluated by the\nbuilt-in function ``input()`` is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes generator expressions since\nthey are implemented using a function scope. This means that the\nfollowing will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nIf a name is bound in a block, it is a local variable of that block.\nIf a name is bound at the module level, it is a global variable. (The\nvariables of the module code block are local and global.) If a\nvariable is used in a code block but not defined there, it is a *free\nvariable*.\n\nWhen a name is not found at all, a ``NameError`` exception is raised.\nIf the name refers to a local variable that has not been bound, a\n``UnboundLocalError`` exception is raised. ``UnboundLocalError`` is a\nsubclass of ``NameError``.\n\nThe following constructs bind names: formal parameters to functions,\n``import`` statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, ``for`` loop header, in the\nsecond position of an ``except`` clause header or after ``as`` in a\n``with`` statement. The ``import`` statement of the form ``from ...\nimport *`` binds all names defined in the imported module, except\nthose beginning with an underscore. This form may only be used at the\nmodule level.\n\nA target occurring in a ``del`` statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name). It\nis illegal to unbind a name that is referenced by an enclosing scope;\nthe compiler will report a ``SyntaxError``.\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the global statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtins namespace, the namespace\nof the module ``__builtin__``. The global namespace is searched\nfirst. If the name is not found there, the builtins namespace is\nsearched. The global statement must precede all uses of the name.\n\nThe builtins namespace associated with the execution of a code block\nis actually found by looking up the name ``__builtins__`` in its\nglobal namespace; this should be a dictionary or a module (in the\nlatter case the module\'s dictionary is used). By default, when in the\n``__main__`` module, ``__builtins__`` is the built-in module\n``__builtin__`` (note: no \'s\'); when in any other module,\n``__builtins__`` is an alias for the dictionary of the ``__builtin__``\nmodule itself. ``__builtins__`` can be set to a user-created\ndictionary to create a weak form of restricted execution.\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\noperation in the same block. If the nearest enclosing scope for a\nfree variable contains a global statement, the free variable is\ntreated 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\nnamespace for the ``exec``. (In other words, ``exec obj`` would be\nillegal, but ``exec obj in ns`` would be legal.)\n\nThe ``eval()``, ``execfile()``, and ``input()`` functions and the\n``exec`` statement do not have access to the full environment for\nresolving names. Names may be resolved in the local and global\nnamespaces of the caller. Free variables are not resolved in the\nnearest enclosing namespace, but in the global namespace. [1] The\n``exec`` statement and the ``eval()`` and ``execfile()`` functions\nhave optional arguments to override the global and local namespace.\nIf only one namespace is specified, it is used for both.\n\n\nExceptions\n==========\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the ``raise`` statement. Exception\nhandlers are specified with the ``try`` ... ``except`` statement. The\n``finally`` clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n``SystemExit``.\n\nExceptions are identified by class instances. The ``except`` clause\nis selected depending on the class of the instance: it must reference\nthe class of the instance or a base class thereof. The instance can\nbe received by the handler and can carry additional information about\nthe exceptional condition.\n\nExceptions can also be identified by strings, in which case the\n``except`` clause is selected by object identity. An arbitrary value\ncan be raised along with the identifying string which can be passed to\nthe handler.\n\nNote: Messages to exceptions are not part of the Python API. Their\n contents may change from one version of Python to the next without\n warning and should not be relied on by code which will run under\n multiple versions of the interpreter.\n\nSee also the description of the ``try`` statement in section *The try\nstatement* and ``raise`` statement in section *The raise statement*.\n\n-[ Footnotes ]-\n\n[1] This limitation occurs because the code that is executed by these\n operations is not available at the time the module is compiled.\n',
51 'naming': u"\nNaming and binding\n******************\n\n*Names* refer to objects. Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block. A script\nfile (a file given as standard input to the interpreter or specified\non the interpreter command line the first argument) is a code block.\nA script command (a command specified on the interpreter command line\nwith the '**-c**' option) is a code block. The file read by the\nbuilt-in function ``execfile()`` is a code block. The string argument\npassed to the built-in function ``eval()`` and to the ``exec``\nstatement is a code block. The expression read and evaluated by the\nbuilt-in function ``input()`` is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block's execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes generator expressions since\nthey are implemented using a function scope. This means that the\nfollowing will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block's *environment*.\n\nIf a name is bound in a block, it is a local variable of that block.\nIf a name is bound at the module level, it is a global variable. (The\nvariables of the module code block are local and global.) If a\nvariable is used in a code block but not defined there, it is a *free\nvariable*.\n\nWhen a name is not found at all, a ``NameError`` exception is raised.\nIf the name refers to a local variable that has not been bound, a\n``UnboundLocalError`` exception is raised. ``UnboundLocalError`` is a\nsubclass of ``NameError``.\n\nThe following constructs bind names: formal parameters to functions,\n``import`` statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, ``for`` loop header, in the\nsecond position of an ``except`` clause header or after ``as`` in a\n``with`` statement. The ``import`` statement of the form ``from ...\nimport *`` binds all names defined in the imported module, except\nthose beginning with an underscore. This form may only be used at the\nmodule level.\n\nA target occurring in a ``del`` statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name). It\nis illegal to unbind a name that is referenced by an enclosing scope;\nthe compiler will report a ``SyntaxError``.\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the global statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtins namespace, the namespace\nof the module ``__builtin__``. The global namespace is searched\nfirst. If the name is not found there, the builtins namespace is\nsearched. The global statement must precede all uses of the name.\n\nThe builtins namespace associated with the execution of a code block\nis actually found by looking up the name ``__builtins__`` in its\nglobal namespace; this should be a dictionary or a module (in the\nlatter case the module's dictionary is used). By default, when in the\n``__main__`` module, ``__builtins__`` is the built-in module\n``__builtin__`` (note: no 's'); when in any other module,\n``__builtins__`` is an alias for the dictionary of the ``__builtin__``\nmodule itself. ``__builtins__`` can be set to a user-created\ndictionary to create a weak form of restricted execution.\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\noperation in the same block. If the nearest enclosing scope for a\nfree variable contains a global statement, the free variable is\ntreated 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\nnamespace for the ``exec``. (In other words, ``exec obj`` would be\nillegal, but ``exec obj in ns`` would be legal.)\n\nThe ``eval()``, ``execfile()``, and ``input()`` functions and the\n``exec`` statement do not have access to the full environment for\nresolving names. Names may be resolved in the local and global\nnamespaces of the caller. Free variables are not resolved in the\nnearest enclosing namespace, but in the global namespace. [1] The\n``exec`` statement and the ``eval()`` and ``execfile()`` functions\nhave optional arguments to override the global and local namespace.\nIf only one namespace is specified, it is used for both.\n",
53 'numeric-types': u'\nEmulating numeric types\n***********************\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``//``, ``%``, ``divmod()``,\n ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``). For\n instance, to evaluate the expression ``x + y``, where *x* is an\n instance of a class that has an ``__add__()`` method,\n ``x.__add__(y)`` is called. The ``__divmod__()`` method should be\n the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n should not be related to ``__truediv__()`` (described below). Note\n that ``__pow__()`` should be defined to accept an optional third\n argument if the ternary version of the built-in ``pow()`` function\n is to be supported.\n\n If one of those methods does not support the operation with the\n supplied arguments, it should return ``NotImplemented``.\n\nobject.__div__(self, other)\nobject.__truediv__(self, other)\n\n The division operator (``/``) is implemented by these methods. The\n ``__truediv__()`` method is used when ``__future__.division`` is in\n effect, otherwise ``__div__()`` is used. If only one of these two\n methods is defined, the object will not support division in the\n alternate context; ``TypeError`` will be raised instead.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rdiv__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``%``, ``divmod()``,\n ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``) with\n reflected (swapped) operands. These functions are only called if\n the left operand does not support the corresponding operation and\n the operands are of different types. [2] For instance, to evaluate\n the expression ``x - y``, where *y* is an instance of a class that\n has an ``__rsub__()`` method, ``y.__rsub__(x)`` is called if\n ``x.__sub__(y)`` returns *NotImplemented*.\n\n Note that ternary ``pow()`` will not try calling ``__rpow__()``\n (the coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left operand\'s\n type and that subclass provides the reflected method for the\n operation, this method will be called before the left operand\'s\n non-reflected method. This behavior allows subclasses to\n override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__idiv__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n These methods are called to implement the augmented arithmetic\n assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``). These methods\n should attempt to do the operation in-place (modifying *self*) and\n return the result (which could be, but does not have to be,\n *self*). If a specific method is not defined, the augmented\n assignment
61 'sequence-methods': u'\nAdditional methods for emulation of sequence types\n**************************************************\n\nThe following optional methods can be defined to further emulate\nsequence objects. Immutable sequences methods should at most only\ndefine ``__getslice__()``; mutable sequences might define all three\nmethods.\n\nobject.__getslice__(self, i, j)\n\n Deprecated since version 2.0: Support slice objects as parameters\n to the ``__getitem__()`` method. (However, built-in types in\n CPython currently still implement ``__getslice__()``. Therefore,\n you have to override it in derived classes when implementing\n slicing.)\n\n Called to implement evaluation of ``self[i:j]``. The returned\n object should be of the same type as *self*. Note that missing *i*\n or *j* in the slice expression are replaced by zero or\n ``sys.maxint``, respectively. If negative indexes are used in the\n slice, the length of the sequence is added to that index. If the\n instance does not implement the ``__len__()`` method, an\n ``AttributeError`` is raised. No guarantee is made that indexes\n adjusted this way are not still negative. Indexes which are\n greater than the length of the sequence are not modified. If no\n ``__getslice__()`` is found, a slice object is created instead, and\n passed to ``__getitem__()`` instead.\n\nobject.__setslice__(self, i, j, sequence)\n\n Called to implement assignment to ``self[i:j]``. Same notes for *i*\n and *j* as for ``__getslice__()``.\n\n This method is deprecated. If no ``__setslice__()`` is found, or\n for extended slicing of the form ``self[i:j:k]``, a slice object is\n created, and passed to ``__setitem__()``, instead of\n ``__setslice__()`` being called.\n\nobject.__delslice__(self, i, j)\n\n Called to implement deletion of ``self[i:j]``. Same notes for *i*\n and *j* as for ``__getslice__()``. This method is deprecated. If no\n ``__delslice__()`` is found, or for extended slicing of the form\n ``self[i:j:k]``, a slice object is created, and passed to\n ``__delitem__()``, instead of ``__delslice__()`` being called.\n\nNotice that these methods are only invoked when a single slice with a\nsingle colon is used, and the slice method is available. For slice\noperations involving extended slice notation, or in absence of the\nslice methods, ``__getitem__()``, ``__setitem__()`` or\n``__delitem__()`` is called with a slice object as argument.\n\nThe following example demonstrate how to make your program or module\ncompatible with earlier versions of Python (assuming that methods\n``__getitem__()``, ``__setitem__()`` and ``__delitem__()`` support\nslice objects as arguments):\n\n class MyClass:\n ...\n def __getitem__(self, index):\n ...\n def __setitem__(self, index, value):\n ...\n def __delitem__(self, index):\n ...\n\n if sys.version_info < (2, 0):\n # They won\'t be defined if version is at least 2.0 final\n\n def __getslice__(self, i, j):\n return self[max(0, i):max(0, j):]\n def __setslice__(self, i, j, seq):\n self[max(0, i):max(0, j):] = seq\n def __delslice__(self, i, j):\n del self[max(0, i):max(0, j):]\n ...\n\nNote the calls to ``max()``; these are necessary because of the\nhandling of negative indices before the ``__*slice__()`` methods are\ncalled. When negative indexes are used, the ``__*item__()`` methods\nreceive them as provided, but the ``__*slice__()`` methods get a\n"cooked" form of the index values. For each negative index value, the\nlength of the sequence is added to the index before calling the method\n(which may still result in a negative index); this is the customary\nhandling of negative indexes by the built-in sequence types, and the\n``__*item__()`` methods are expected to do this as well. However,\nsince they should already be doing that, negative indexes cannot be\npassed in; they must be constrained to the bounds of the sequence\nbefore being passed to the ``__*item__()`` methods. Calling ``max(0,\ni)`` conveniently returns the proper value.\n',
62 'sequence-types': u"\nEmulating container types\n*************************\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well. The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. (For backwards compatibility, the method\n``__getslice__()`` (see below) can also be defined to handle simple,\nbut not extended slices.) It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``has_key()``,\n``get()``, ``clear()``, ``setdefault()``, ``iterkeys()``,\n``itervalues()``, ``iteritems()``, ``pop()``, ``popitem()``,\n``copy()``, and ``update()`` behaving similar to those for Python's\nstandard dictionary objects. The ``UserDict`` module provides a\n``DictMixin`` class to help create those methods from a base set of\n``__getitem__()``, ``__setitem__()``, ``__delitem__()``, and\n``keys()``. Mutable sequences should provide methods ``append()``,\n``count()``, ``index()``, ``extend()``, ``insert()``, ``pop()``,\n``remove()``, ``reverse()`` and ``sort()``, like Python standard list\nobjects. Finally, sequence types should implement addition (meaning\nconcatenation) and multiplication (meaning repetition) by defining the\nmethods ``__add__()``, ``__radd__()``, ``__iadd__()``, ``__mul__()``,\n``__rmul__()`` and ``__imul__()`` described below; they should not\ndefine ``__coerce__()`` or other numerical operators. It is\nrecommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should be equivalent of ``has_key()``;\nfor sequences, it should search through the values. It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``iterkeys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n Called to implement the built-in function ``len()``. Should return\n the length of the object, an integer ``>=`` 0. Also, an object\n that doesn't define a ``__nonzero__()`` method and whose\n ``__len__()`` method returns zero is considered to be false in a\n Boolean context.\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of ``self[key]``. For sequence\n types, the accepted keys should be integers and slice objects.\n Note that the special interpretation of negative indexes (if the\n class wishes to emulate a sequence type) is up to the\n ``__getitem__()`` method. If *key* is of an inappropriate type,\n ``TypeError`` may be raised; if of a value outside the set of\n indexes for the sequence (after any special interpretation of\n negative values), ``IndexError`` should be raised. For mapping\n types, if *key* is missing (not in the container), ``KeyError``\n should be raised.\n\n Note: ``for`` loops expect that an ``IndexError`` will be raised for\n illegal indexes to allow proper detection of the end of the\n sequence.\n\nobject.__setitem__(self, key, value)\n\n Called to implement assignment to ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support changes to the values for keys, or if new keys\n can be added, or for sequences if elements can be replaced. The\n same exceptions should be raised for improper *key* values as for\n the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n Called to implement deletion of ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support removal of keys, or for sequences if elements\n can be removed from the sequence. The same exceptions should be\n raised for improper *key* values as for the ``__getitem__()``\n method.\n\nobject.__iter__(self)\n\n This method is called when an iterator is required for a container.\n This method should return a new iterator object that can iterate\n over all the objects in the container. For mappings, it should\n iterate over the keys of the container, and should also be made\n available as the method ``iterkeys()``.\n\n Iterator objects also need to implement this method; they are\n required to return themselves. For more information on iterator\n objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n Called (if present) by the ``reversed()`` built-in to implement\n reverse iteration. It should return a new iterator object that\n iterates over all the objects in the container in reverse order.\n\n If the ``__reversed__()`` method is not provided, the\n ``reversed()`` built-in will fall back to using the sequence\n protocol (``__len__()`` and ``__getitem__()``). Objects that\n support the sequence protocol should only provide\n ``__reversed__()`` if they can provide an implementation that is\n more efficient than the one provided by ``reversed()``.\n\n New in version 2.6.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence. However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n Called to implement membership test operators. Should return true\n if *item* is in *self*, false otherwise. For mapping objects, this\n should consider the keys of the mapping rather than the values or\n the key-item pairs.\n\n For objects that don't define ``__contains__()``, the membership\n test first tries iteration via ``__iter__()``, then the old\n sequence iteration protocol via ``__getitem__()``, see *this\n section in the language reference*.\n",
64 'slicings': u'\nSlicings\n********\n\nA slicing selects a range of items in a sequence object (e.g., a\nstring, tuple or list). Slicings may be used as expressions or as\ntargets in assignment
66 assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control in new-style classes.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should not simply execute ``self.name = value`` --- this would\n cause a recursive call to itself. Instead, it should insert the\n value in the dictionary of instance attributes, e.g.,\n ``self.__dict__[name] = value``. For new-style classes, rather\n than accessing the instance dictionary, it should call the base\n class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignment. This should only be implemented if ``del obj.name`` is\n meaningful for the object.\n\n\nMore attribute access for new-style classes\n-------------------------------------------\n\nThe following methods only apply to new-style classes.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines\n ``__getattr__()``, the latter will not be called unless\n ``__getattribute__()`` either calls it explicitly or raises an\n ``AttributeError``. This method should return the (computed)\n attribute value or raise an ``AttributeError`` exception. In order\n to avoid infinite recursion in this method, its implementation\n should always call the base class method with the same name to\n access any attributes it needs, for example,\n ``object.__getattribute__(self, name)``.\n\n Note: This method may still be bypassed when looking up special methods\n as the result of implicit invocation via language syntax or\n built-in functions. See *Special method lookup for new-style\n classes*.\n\n\nImplementing Descriptors\n------------------------\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in 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\n ``AttributeError`` 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,\nit is 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\n``type()``).\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the 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\n ``A`` immediately preceding ``B`` and then invokes the descriptor\n with the 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__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary. If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor. Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method. Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary. In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented 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 defining\n *__slots__* do not support weak references to its instances. If weak\n reference support is needed, then add ``\'__weakref__\'`` to the\n sequence of strings in the *__slots__* 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\n a 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 instance\n variable defined by the base class slot is inaccessible (except by\n retrieving its descriptor directly from the base class). This\n 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\n ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n 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__* assignmentassignment to ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support changes to the values for keys, or if new keys\n can be added, or for sequences if elements can be replaced. The\n same exceptions should be raised for improper *key* values as for\n the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n Called to implement deletion of ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support removal of keys, or for sequences if elements\n can be removed from the sequence. The same exceptions should be\n raised for improper *key* values as for the ``__getitem__()``\n method.\n\nobject.__iter__(self)\n\n This method is called when an iterator is required for a container.\n This method should return a new iterator object that can iterate\n over all the objects in the container. For mappings, it should\n iterate over the keys of the container, and should also be made\n available as the method ``iterkeys()``.\n\n Iterator objects also need to implement this method; they are\n required to return themselves. For more information on iterator\n objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n Called (if present) by the ``reversed()`` built-in to implement\n reverse iteration. It should return a new iterator object that\n iterates over all the objects in the container in reverse order.\n\n If the ``__reversed__()`` method is not provided, the\n ``reversed()`` built-in will fall back to using the sequence\n protocol (``__len__()`` and ``__getitem__()``). Objects that\n support the sequence protocol should only provide\n ``__reversed__()`` if they can provide an implementation that is\n more efficient than the one provided by ``reversed()``.\n\n New in version 2.6.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence. However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n Called to implement membership test operators. Should return true\n if *item* is in *self*, false otherwise. For mapping objects, this\n should consider the keys of the mapping rather than the values or\n the key-item pairs.\n\n For objects that don\'t define ``__contains__()``, the membership\n test first tries iteration via ``__iter__()``, then the old\n sequence iteration protocol via ``__getitem__()``, see *this\n section in the language reference*.\n\n\nAdditional methods for emulation of sequence types\n==================================================\n\nThe following optional methods can be defined to further emulate\nsequence objects. Immutable sequences methods should at most only\ndefine ``__getslice__()``; mutable sequences might define all three\nmethods.\n\nobject.__getslice__(self, i, j)\n\n Deprecated since version 2.0: Support slice objects as parameters\n to the ``__getitem__()`` method. (However, built-in types in\n CPython currently still implement ``__getslice__()``. Therefore,\n you have to override it in derived classes when implementing\n slicing.)\n\n Called to implement evaluation of ``self[i:j]``. The returned\n object should be of the same type as *self*. Note that missing *i*\n or *j* in the slice expression are replaced by zero or\n ``sys.maxint``, respectively. If negative indexes are used in the\n slice, the length of the sequence is added to that index. If the\n instance does not implement the ``__len__()`` method, an\n ``AttributeError`` is raised. No guarantee is made that indexes\n adjusted this way are not still negative. Indexes which are\n greater than the length of the sequence are not modified. If no\n ``__getslice__()`` is found, a slice object is created instead, and\n passed to ``__getitem__()`` instead.\n\nobject.__setslice__(self, i, j, sequence)\n\n Called to implement assignment to ``self[i:j]``. Same notes for *i*\n and *j* as for ``__getslice__()``.\n\n This method is deprecated. If no ``__setslice__()`` is found, or\n for extended slicing of the form ``self[i:j:k]``, a slice object is\n created, and passed to ``__setitem__()``, instead of\n ``__setslice__()`` being called.\n\nobject.__delslice__(self, i, j)\n\n Called to implement deletion of ``self[i:j]``. Same notes for *i*\n and *j* as for ``__getslice__()``. This method is deprecated. If no\n ``__delslice__()`` is found, or for extended slicing of the form\n ``self[i:j:k]``, a slice object is created, and passed to\n ``__delitem__()``, instead of ``__delslice__()`` being called.\n\nNotice that these methods are only invoked when a single slice with a\nsingle colon is used, and the slice method is available. For slice\noperations involving extended slice notation, or in absence of the\nslice methods, ``__getitem__()``, ``__setitem__()`` or\n``__delitem__()`` is called with a slice object as argument.\n\nThe following example demonstrate how to make your program or module\ncompatible with earlier versions of Python (assuming that methods\n``__getitem__()``, ``__setitem__()`` and ``__delitem__()`` support\nslice objects as arguments):\n\n class MyClass:\n ...\n def __getitem__(self, index):\n ...\n def __setitem__(self, index, value):\n ...\n def __delitem__(self, index):\n ...\n\n if sys.version_info < (2, 0):\n # They won\'t be defined if version is at least 2.0 final\n\n def __getslice__(self, i, j):\n return self[max(0, i):max(0, j):]\n def __setslice__(self, i, j, seq):\n self[max(0, i):max(0, j):] = seq\n def __delslice__(self, i, j):\n del self[max(0, i):max(0, j):]\n ...\n\nNote the calls to ``max()``; these are necessary because of the\nhandling of negative indices before the ``__*slice__()`` methods are\ncalled. When negative indexes are used, the ``__*item__()`` methods\nreceive them as provided, but the ``__*slice__()`` methods get a\n"cooked" form of the index values. For each negative index value, the\nlength of the sequence is added to the index before calling the method\n(which may still result in a negative index); this is the customary\nhandling of negative indexes by the built-in sequence types, and the\n``__*item__()`` methods are expected to do this as well. However,\nsince they should already be doing that, negative indexes cannot be\npassed in; they must be constrained to the bounds of the sequence\nbefore being passed to the ``__*item__()`` methods. Calling ``max(0,\ni)`` conveniently returns the proper value.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``//``, ``%``, ``divmod()``,\n ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``). For\n instance, to evaluate the expression ``x + y``, where *x* is an\n instance of a class that has an ``__add__()`` method,\n ``x.__add__(y)`` is called. The ``__divmod__()`` method should be\n the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n should not be related to ``__truediv__()`` (described below). Note\n that ``__pow__()`` should be defined to accept an optional third\n argument if the ternary version of the built-in ``pow()`` function\n is to be supported.\n\n If one of those methods does not support the operation with the\n supplied arguments, it should return ``NotImplemented``.\n\nobject.__div__(self, other)\nobject.__truediv__(self, other)\n\n The division operator (``/``) is implemented by these methods. The\n ``__truediv__()`` method is used when ``__future__.division`` is in\n effect, otherwise ``__div__()`` is used. If only one of these two\n methods is defined, the object will not support division in the\n alternate context; ``TypeError`` will be raised instead.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rdiv__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``%``, ``divmod()``,\n ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``) with\n reflected (swapped) operands. These functions are only called if\n the left operand does not support the corresponding operation and\n the operands are of different types. [2] For instance, to evaluate\n the expression ``x - y``, where *y* is an instance of a class that\n has an ``__rsub__()`` method, ``y.__rsub__(x)`` is called if\n ``x.__sub__(y)`` returns *NotImplemented*.\n\n Note that ternary ``pow()`` will not try calling ``__rpow__()``\n (the coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left operand\'s\n type and that subclass provides the reflected method for the\n operation, this method will be called before the left operand\'s\n non-reflected method. This behavior allows subclasses to\n override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__idiv__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n These methods are called to implement the augmented arithmetic\n assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``). These methods\n should attempt to do the operation in-place (modifying *self*) and\n return the result (which could be, but does not have to be,\n *self*). If a specific method is not defined, the augmented\n assignment
73 assignmentassignment
82 'with': u'\nThe ``with`` statement\n**********************\n\nNew in version 2.5.\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" 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\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nNote: In Python 2.5, the ``with`` statement is only allowed when the\n ``with_statement`` feature has been enabled. It is always enabled\n in Python 2.6.\n\nChanged in version 2.7: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n',