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author	Martin Panter <vadmium+py@gmail.com>	2016-09-11 09:32:26 (GMT)
committer	Martin Panter <vadmium+py@gmail.com>	2016-09-11 09:32:26 (GMT)
commit	b7665386bc64e8f816a14ef63b72881a00a4d08b (patch)
tree	aaa4212e44337740d3c9bfddbbfb94017ff41bd5 /Lib/test/test_unicode_file_functions.py
parent	53ba2d10e0d94a7609c0a71d41956a58e6a68f9d (diff)
download	cpython-b7665386bc64e8f816a14ef63b72881a00a4d08b.zip cpython-b7665386bc64e8f816a14ef63b72881a00a4d08b.tar.gz cpython-b7665386bc64e8f816a14ef63b72881a00a4d08b.tar.bz2

Issue #27952: Get fixcid.py working with the re module

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lass="hl str">implementation, the built-in variable ``__debug__`` is ``True`` under\nnormal circumstances, ``False`` when optimization is requested\n(command line option -O). The current code generator emits no code\nfor an assert statement when optimization is requested at compile\ntime. Note that it is unnecessary to include the source code for the\nexpression that failed in the error message; it will be displayed as\npart of the stack trace.\n\nAssignments to ``__debug__`` are illegal. The value for the built-in\nvariable is determined when the interpreter starts.\n', 'assignment': '\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 | "*" target\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, optionally enclosed in\nparentheses or square brackets, is recursively defined as follows.\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:\n\n * If the target list contains one target prefixed with an asterisk,\n called a "starred" target: The object must be a sequence with at\n least as many items as there are targets in the target list, minus\n one. The first items of the sequence are assigned, from left to\n right, to the targets before the starred target. The final items\n of the sequence are assigned to the targets after the starred\n target. A list of the remaining items in the sequence is then\n assigned to the starred target (the list can be empty).\n\n * Else: The object must be a sequence with the same number of items\n as there are targets in the target list, and the items are\n assigned, from 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`` or ``nonlocal``\n statement in the current code block: the name is bound to the\n object in the current local namespace.\n\n * Otherwise: the name is bound to the object in the global namespace\n or the outer namespace determined by ``nonlocal``, respectively.\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 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 a sequence 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* 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 an integer. If it is negative, the sequence\'s\n length is added to it. The resulting value must be a nonnegative\n integer less than the sequence\'s length, and the sequence is asked\n to assign the assigned object to its item with that index. If the\n index is out of range, ``IndexError`` is raised (assignment to a\n subscripted sequence cannot add new items to a 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 For user-defined objects, the ``__setitem__()`` method is called\n with appropriate arguments.\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 integers. If either bound is\n negative, the sequence\'s length is added to it. The resulting\n bounds are clipped to lie between zero and the sequence\'s length,\n inclusive. Finally, the sequence object is asked to replace the\n slice with the items of the assigned sequence. The length of the\n 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(In the current implementation, the syntax for targets is taken to be\nthe same as for expressions, and invalid syntax is rejected during the\ncode generation phase, causing less 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\nSee also:\n\n **PEP 3132** - Extended Iterable Unpacking\n The specification for the ``*target`` feature.\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 ::= target augop (expression_list | yield_expression)\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 initial value is\nretrieved with a ``getattr()`` and the result is assigned with a\n``setattr()``. Notice that the two methods do not necessarily refer\nto the same variable. When ``getattr()`` refers to a class variable,\n``setattr()`` still writes to an instance variable. For example:\n\n class A:\n x = 3 # class variable\n a = A()\n a.x += 1 # writes a.x as 4 leaving A.x as 3\n', 'atom-identifiers': '\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name. See section\n*Identifiers and keywords* for lexical definition and section *Naming\nand binding* for documentation of naming and binding.\n\nWhen the name is bound to an object, evaluation of the atom yields\nthat object. When a name is not bound, an attempt to evaluate it\nraises a ``NameError`` exception.\n\n**Private name mangling:** When an identifier that textually occurs in\na class definition begins with two or more underscore characters and\ndoes not end in two or more underscores, it is considered a *private\nname* of that class. Private names are transformed to a longer form\nbefore code is generated for them. The transformation inserts the\nclass name in front of the name, with leading underscores removed, and\na single underscore inserted in front of the class name. For example,\nthe identifier ``__spam`` occurring in a class named ``Ham`` will be\ntransformed to ``_Ham__spam``. This transformation is independent of\nthe syntactical context in which the identifier is used. If the\ntransformed name is extremely long (longer than 255 characters),\nimplementation defined truncation may happen. If the class name\nconsists only of underscores, no transformation is done.\n', 'atom-literals': "\nLiterals\n********\n\nPython supports string and bytes literals and various numeric\nliterals:\n\n literal ::= stringliteral | bytesliteral\n | integer | floatnumber | imagnumber\n\nEvaluation of a literal yields an object of the given type (string,\nbytes, integer, floating point number, complex number) with the given\nvalue. The value may be approximated in the case of floating point\nand imaginary (complex) literals. See section *Literals* for details.\n\nWith the exception of bytes literals, these all correspond to\nimmutable data types, and hence the object's identity is less\nimportant than its value. Multiple evaluations of literals with the\nsame value (either the same occurrence in the program text or a\ndifferent occurrence) may obtain the same object or a different object\nwith the same value.\n", 'attribute-access': '\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 over attribute access.\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 builtin functions. See *Special method lookup*.\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 call the base 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\nobject.__dir__(self)\n\n Called when ``dir()`` is called on the object. A list must be\n returned.\n\n\nImplementing Descriptors\n========================\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in the\nclass dictionary of another class, known as the *owner* class. 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.\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 an object instance, ``a.x`` is transformed into the\n call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n If binding to a class, ``A.x`` is transformed into the call:\n ``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, A)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. Normally, data\ndescriptors define both ``__get__()`` and ``__set__()``, while non-\ndata descriptors have just the ``__get__()`` method. Data descriptors\nalways override a redefinition in an instance dictionary. In\ncontrast, non-data descriptors can be overridden by instances. [2]\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 classes have a dictionary for attribute\nstorage. This wastes space for objects having very few instance\nvariables. The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable. Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__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 class, *__slots__* reserves space for the declared variables and\n prevents the automatic creation of *__dict__* and *__weakref__* for\n each instance.\n\n\nNotes on using *__slots__*\n--------------------------\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* 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* *__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* 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* 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__*.\n\n* Nonempty *__slots__* does not work for classes derived from\n "variable-length" built-in types such as ``int``, ``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', 'attribute-references': '\nAttribute references\n********************\n\nAn attribute reference is a primary followed by a period and a name:\n\n attributeref ::= primary "." identifier\n\nThe primary must evaluate to an object of a type that supports\nattribute references, which most objects do. This object is then\nasked to produce the attribute whose name is the identifier (which can\nbe customized by overriding the ``__getattr__()`` method). If this\nattribute is not available, the exception ``AttributeError`` is\nraised. Otherwise, the type and value of the object produced is\ndetermined by the object. Multiple evaluations of the same attribute\nreference may yield different objects.\n', 'augassign': '\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 ::= target augop (expression_list | yield_expression)\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 initial value is\nretrieved with a ``getattr()`` and the result is assigned with a\n``setattr()``. Notice that the two methods do not necessarily refer\nto the same variable. When ``getattr()`` refers to a class variable,\n``setattr()`` still writes to an instance variable. For example:\n\n class A:\n x = 3 # class variable\n a = A()\n a.x += 1 # writes a.x as 4 leaving A.x as 3\n', 'binary': '\nBinary arithmetic operations\n****************************\n\nThe binary arithmetic operations have the conventional priority\nlevels. Note that some of these operations also apply to certain non-\nnumeric types. Apart from the power operator, there are only two\nlevels, one for multiplicative operators and one for additive\noperators:\n\n m_expr ::= u_expr | m_expr "*" u_expr | m_expr "//" u_expr | m_expr "/" u_expr\n | m_expr "%" u_expr\n a_expr ::= m_expr | a_expr "+" m_expr | a_expr "-" m_expr\n\nThe ``*`` (multiplication) operator yields the product of its\narguments. The arguments must either both be numbers, or one argument\nmust be an integer and the other must be a sequence. In the former\ncase, the numbers are converted to a common type and then multiplied\ntogether. In the latter case, sequence repetition is performed; a\nnegative repetition factor yields an empty sequence.\n\nThe ``/`` (division) and ``//`` (floor division) operators yield the\nquotient of their arguments. The numeric arguments are first\nconverted to a common type. Integer division yields a float, while\nfloor division of integers results in an integer; the result is that\nof mathematical division with the \'floor\' function applied to the\nresult. Division by zero raises the ``ZeroDivisionError`` exception.\n\nThe ``%`` (modulo) operator yields the remainder from the division of\nthe first argument by the second. The numeric arguments are first\nconverted to a common type. A zero right argument raises the\n``ZeroDivisionError`` exception. The arguments may be floating point\nnumbers, e.g., ``3.14%0.7`` equals ``0.34`` (since ``3.14`` equals\n``4*0.7 + 0.34``.) The modulo operator always yields a result with\nthe same sign as its second operand (or zero); the absolute value of\nthe result is strictly smaller than the absolute value of the second\noperand [1].\n\nThe floor division and modulo operators are connected by the following\nidentity: ``x == (x//y)*y + (x%y)``. Floor division and modulo are\nalso connected with the built-in function ``divmod()``: ``divmod(x, y)\n== (x//y, x%y)``. [2].\n\nIn addition to performing the modulo operation on numbers, the ``%``\noperator is also overloaded by string objects to perform old-style\nstring formatting (also known as interpolation). The syntax for\nstring formatting is described in the Python Library Reference,\nsection *Old String Formatting Operations*.\n\nThe floor division operator, the modulo operator, and the ``divmod()``\nfunction are not defined for complex numbers. Instead, convert to a\nfloating point number using the ``abs()`` function if appropriate.\n\nThe ``+`` (addition) operator yields the sum of its arguments. The\narguments must either both be numbers or both sequences of the same\ntype. In the former case, the numbers are converted to a common type\nand then added together. In the latter case, the sequences are\nconcatenated.\n\nThe ``-`` (subtraction) operator yields the difference of its\narguments. The numeric arguments are first converted to a common\ntype.\n', 'bitwise': '\nBinary bitwise operations\n*************************\n\nEach of the three bitwise operations has a different priority level:\n\n and_expr ::= shift_expr | and_expr "&" shift_expr\n xor_expr ::= and_expr | xor_expr "^" and_expr\n or_expr ::= xor_expr | or_expr "|" xor_expr\n\nThe ``&`` operator yields the bitwise AND of its arguments, which must\nbe integers.\n\nThe ``^`` operator yields the bitwise XOR (exclusive OR) of its\narguments, which must be integers.\n\nThe ``|`` operator yields the bitwise (inclusive) OR of its arguments,\nwhich must be integers.\n', 'bltin-code-objects': '\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 ``__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()`` or ``eval()`` built-in functions.\n\nSee *The standard type hierarchy* for more information.\n', 'bltin-ellipsis-object': '\nThe Ellipsis Object\n*******************\n\nThis object is commonly used by slicing (see *Slicings*). It supports\nno special operations. There is exactly one ellipsis object, named\n``Ellipsis`` (a built-in name).\n\nIt is written as ``Ellipsis`` or ``...``.\n', 'bltin-file-objects': '\nFile Objects\n************\n\nFile objects are implemented using C\'s ``stdio`` package and can be\ncreated with the built-in ``open()`` function. File objects are also\nreturned by some other built-in functions and methods, such as\n``os.popen()`` and ``os.fdopen()`` and the ``makefile()`` method of\nsocket objects. Temporary files can be created using the ``tempfile``\nmodule, and high-level file operations such as copying, moving, and\ndeleting files and directories can be achieved with the ``shutil``\nmodule.\n\nWhen a file operation fails for an I/O-related reason, the exception\n``IOError`` is raised. This includes situations where the operation\nis not defined for some reason, like ``seek()`` on a tty device or\nwriting a file opened for reading.\n\nFiles have the following methods:\n\nfile.close()\n\n Close the file. A closed file cannot be read or written any more.\n Any operation which requires that the file be open will raise a\n ``ValueError`` after the file has been closed. Calling ``close()``\n more than once is allowed.\n\n You can avoid having to call this method explicitly if you use the\n ``with`` statement. For example, the following code will\n automatically close *f* when the ``with`` block is exited:\n\n from __future__ import with_statement # This isn\'t required in Python 2.6\n\n with open("hello.txt") as f:\n for line in f:\n print(line)\n\n In older versions of Python, you would have needed to do this to\n get the same effect:\n\n f = open("hello.txt")\n try:\n for line in f:\n print(line)\n finally:\n f.close()\n\n Note: Not all "file-like" types in Python support use as a context\n manager for the ``with`` statement. If your code is intended to\n work with any file-like object, you can use the function\n ``contextlib.closing()`` instead of using the object directly.\n\nfile.flush()\n\n Flush the internal buffer, like ``stdio``\'s ``fflush``. This may\n be a no-op on some file-like objects.\n\nfile.fileno()\n\n Return the integer "file descriptor" that is used by the underlying\n implementation to request I/O operations from the operating system.\n This can be useful for other, lower level interfaces that use file\n descriptors, such as the ``fcntl`` module or ``os.read()`` and\n friends.\n\n Note: File-like objects which do not have a real file descriptor should\n *not* provide this method!\n\nfile.isatty()\n\n Return ``True`` if the file is connected to a tty(-like) device,\n else ``False``.\n\n Note: If a file-like object is not associated with a real file, this\n method should *not* be implemented.\n\nfile.__next__()\n\n A file object is its own iterator, for example ``iter(f)`` returns\n *f* (unless *f* is closed). When a file is used as an iterator,\n typically in a ``for`` loop (for example, ``for line in f:\n print(line)``), the ``__next__()`` method is called repeatedly.\n This method returns the next input line, or raises\n ``StopIteration`` when EOF is hit when the file is open for reading\n (behavior is undefined when the file is open for writing). In\n order to make a ``for`` loop the most efficient way of looping over\n the lines of a file (a very common operation), the ``__next__()``\n method uses a hidden read-ahead buffer. As a consequence of using\n a read-ahead buffer, combining ``__next__()`` with other file\n methods (like ``readline()``) does not work right. However, using\n ``seek()`` to reposition the file to an absolute position will\n flush the read-ahead buffer.\n\nfile.read([size])\n\n Read at most *size* bytes from the file (less if the read hits EOF\n before obtaining *size* bytes). If the *size* argument is negative\n or omitted, read all data until EOF is reached. The bytes are\n returned as a string object. An empty string is returned when EOF\n is encountered immediately. (For certain files, like ttys, it\n makes sense to continue reading after an EOF is hit.) Note that\n this method may call the underlying C function ``fread`` more than\n once in an effort to acquire as close to *size* bytes as possible.\n Also note that when in non-blocking mode, less data than was\n requested may be returned, even if no *size* parameter was given.\n\nfile.readline([size])\n\n Read one entire line from the file. A trailing newline character\n is kept in the string (but may be absent when a file ends with an\n incomplete line). [6] If the *size* argument is present and non-\n negative, it is a maximum byte count (including the trailing\n newline) and an incomplete line may be returned. An empty string is\n returned *only* when EOF is encountered immediately.\n\n Note: Unlike ``stdio``\'s ``fgets``, the returned string contains null\n characters (``\'\\0\'``) if they occurred in the input.\n\nfile.readlines([sizehint])\n\n Read until EOF using ``readline()`` and return a list containing\n the lines thus read. If the optional *sizehint* argument is\n present, instead of reading up to EOF, whole lines totalling\n approximately *sizehint* bytes (possibly after rounding up to an\n internal buffer size) are read. Objects implementing a file-like\n interface may choose to ignore *sizehint* if it cannot be\n implemented, or cannot be implemented efficiently.\n\nfile.seek(offset[, whence])\n\n Set the file\'s current position, like ``stdio``\'s ``fseek``. The\n *whence* argument is optional and defaults to ``os.SEEK_SET`` or\n ``0`` (absolute file positioning); other values are ``os.SEEK_CUR``\n or ``1`` (seek relative to the current position) and\n ``os.SEEK_END`` or ``2`` (seek relative to the file\'s end). There\n is no return value.\n\n For example, ``f.seek(2, os.SEEK_CUR)`` advances the position by\n two and ``f.seek(-3, os.SEEK_END)`` sets the position to the third\n to last.\n\n Note that if the file is opened for appending (mode ``\'a\'`` or\n ``\'a+\'``), any ``seek()`` operations will be undone at the next\n write. If the file is only opened for writing in append mode (mode\n ``\'a\'``), this method is essentially a no-op, but it remains useful\n for files opened in append mode with reading enabled (mode\n ``\'a+\'``). If the file is opened in text mode (without ``\'b\'``),\n only offsets returned by ``tell()`` are legal. Use of other\n offsets causes undefined behavior.\n\n Note that not all file objects are seekable.\n\nfile.tell()\n\n Return the file\'s current position, like ``stdio``\'s ``ftell``.\n\n Note: On Windows, ``tell()`` can return illegal values (after an\n ``fgets``) when reading files with Unix-style line-endings. Use\n binary mode (``\'rb\'``) to circumvent this problem.\n\nfile.truncate([size])\n\n Truncate the file\'s size. If the optional *size* argument is\n present, the file is truncated to (at most) that size. The size\n defaults to the current position. The current file position is not\n changed. Note that if a specified size exceeds the file\'s current\n size, the result is platform-dependent: possibilities include that\n the file may remain unchanged, increase to the specified size as if\n zero-filled, or increase to the specified size with undefined new\n content. Availability: Windows, many Unix variants.\n\nfile.write(str)\n\n Write a string to the file. Due to buffering, the string may not\n actually show up in the file until the ``flush()`` or ``close()``\n method is called.\n\n The meaning of the return value is not defined for every file-like\n object. Some (mostly low-level) file-like objects may return the\n number of bytes actually written, others return ``None``.\n\nfile.writelines(sequence)\n\n Write a sequence of strings to the file. The sequence can be any\n iterable object producing strings, typically a list of strings.\n There is no return value. (The name is intended to match\n ``readlines()``; ``writelines()`` does not add line separators.)\n\nFiles support the iterator protocol. Each iteration returns the same\nresult as ``file.readline()``, and iteration ends when the\n``readline()`` method returns an empty string.\n\nFile objects also offer a number of other interesting attributes.\nThese are not required for file-like objects, but should be\nimplemented if they make sense for the particular object.\n\nfile.closed\n\n bool indicating the current state of the file object. This is a\n read-only attribute; the ``close()`` method changes the value. It\n may not be available on all file-like objects.\n\nfile.encoding\n\n The encoding that this file uses. When strings are written to a\n file, they will be converted to byte strings using this encoding.\n In addition, when the file is connected to a terminal, the\n attribute gives the encoding that the terminal is likely to use\n (that information might be incorrect if the user has misconfigured\n the terminal). The attribute is read-only and may not be present\n on all file-like objects. It may also be ``None``, in which case\n the file uses the system default encoding for converting strings.\n\nfile.errors\n\n The Unicode error handler used along with the encoding.\n\nfile.mode\n\n The I/O mode for the file. If the file was created using the\n ``open()`` built-in function, this will be the value of the *mode*\n parameter. This is a read-only attribute and may not be present on\n all file-like objects.\n\nfile.name\n\n If the file object was created using ``open()``, the name of the\n file. Otherwise, some string that indicates the source of the file\n object, of the form ``<...>``. This is a read-only attribute and\n may not be present on all file-like objects.\n\nfile.newlines\n\n If Python was built with the *--with-universal-newlines* option to\n **configure** (the default) this read-only attribute exists, and\n for files opened in universal newline read mode it keeps track of\n the types of newlines encountered while reading the file. The\n values it can take are ``\'\\r\'``, ``\'\\n\'``, ``\'\\r\\n\'``, ``None``\n (unknown, no newlines read yet) or a tuple containing all the\n newline types seen, to indicate that multiple newline conventions\n were encountered. For files not opened in universal newline read\n mode the value of this attribute will be ``None``.\n', 'bltin-null-object': "\nThe Null Object\n***************\n\nThis object is returned by functions that don't explicitly return a\nvalue. It supports no special operations. There is exactly one null\nobject, named ``None`` (a built-in name).\n\nIt is written as ``None``.\n", 'bltin-type-objects': "\nType Objects\n************\n\nType objects represent the various object types. An object's type is\naccessed by the built-in function ``type()``. There are no special\noperations on types. The standard module ``types`` defines names for\nall standard built-in types.\n\nTypes are written like this: ``<class 'int'>``.\n", 'booleans': '\nBoolean operations\n******************\n\nBoolean operations have the lowest priority of all Python operations:\n\n expression ::= conditional_expression | lambda_form\n expression_nocond ::= or_test | lambda_form_nocond\n conditional_expression ::= or_test ["if" or_test "else" expression]\n or_test ::= and_test | or_test "or" and_test\n and_test ::= not_test | and_test "and" not_test\n not_test ::= comparison | "not" not_test\n\nIn the context of Boolean operations, and also when expressions are\nused by control flow statements, the following values are interpreted\nas false: ``False``, ``None``, numeric zero of all types, and empty\nstrings and containers (including strings, tuples, lists,\ndictionaries, sets and frozensets). All other values are interpreted\nas true. User-defined objects can customize their truth value by\nproviding a ``__bool__()`` method.\n\nThe operator ``not`` yields ``True`` if its argument is false,\n``False`` otherwise.\n\nThe expression ``x if C else y`` first evaluates *C* (*not* *x*); if\n*C* is true, *x* is evaluated and its value is returned; otherwise,\n*y* is evaluated and its value is returned.\n\nThe expression ``x and y`` first evaluates *x*; if *x* is false, its\nvalue is returned; otherwise, *y* is evaluated and the resulting value\nis returned.\n\nThe expression ``x or y`` first evaluates *x*; if *x* is true, its\nvalue is returned; otherwise, *y* is evaluated and the resulting value\nis returned.\n\n(Note that neither ``and`` nor ``or`` restrict the value and type they\nreturn to ``False`` and ``True``, but rather return the last evaluated\nargument. This is sometimes useful, e.g., if ``s`` is a string that\nshould be replaced by a default value if it is empty, the expression\n``s or \'foo\'`` yields the desired value. Because ``not`` has to\ninvent a value anyway, it does not bother to return a value of the\nsame type as its argument, so e.g., ``not \'foo\'`` yields ``False``,\nnot ``\'\'``.)\n', 'break': '\nThe ``break`` statement\n***********************\n\n break_stmt ::= "break"\n\n``break`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition\nwithin that loop.\n\nIt terminates the nearest enclosing loop, skipping the optional\n``else`` clause if the loop has one.\n\nIf a ``for`` loop is terminated by ``break``, the loop control target\nkeeps its current value.\n\nWhen ``break`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nleaving the loop.\n', 'callable-types': '\nEmulating callable objects\n**************************\n\nobject.__call__(self[, args...])\n\n Called when the instance is "called" as a function; if this method\n is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n ``x.__call__(arg1, arg2, ...)``.\n', 'calls': '\nCalls\n*****\n\nA call calls a callable object (e.g., a function) with a possibly\nempty series of arguments:\n\n call ::= primary "(" [argument_list [","] | comprehension] ")"\n argument_list ::= positional_arguments ["," keyword_arguments]\n ["," "*" expression] ["," keyword_arguments]\n ["," "**" expression]\n | keyword_arguments ["," "*" expression]\n ["," keyword_arguments] ["," "**" expression]\n | "*" expression ["," keyword_arguments] ["," "**" expression]\n | "**" expression\n positional_arguments ::= expression ("," expression)*\n keyword_arguments ::= keyword_item ("," keyword_item)*\n keyword_item ::= identifier "=" expression\n\nA trailing comma may be present after the positional and keyword\narguments but does not affect the semantics.\n\nThe primary must evaluate to a callable object (user-defined\nfunctions, built-in functions, methods of built-in objects, class\nobjects, methods of class instances, and all objects having a\n``__call__()`` method are callable). All argument expressions are\nevaluated before the call is attempted. Please refer to section\n*Function definitions* for the syntax of formal parameter lists.\n\nIf keyword arguments are present, they are first converted to\npositional arguments, as follows. First, a list of unfilled slots is\ncreated for the formal parameters. If there are N positional\narguments, they are placed in the first N slots. Next, for each\nkeyword argument, the identifier is used to determine the\ncorresponding slot (if the identifier is the same as the first formal\nparameter name, the first slot is used, and so on). If the slot is\nalready filled, a ``TypeError`` exception is raised. Otherwise, the\nvalue of the argument is placed in the slot, filling it (even if the\nexpression is ``None``, it fills the slot). When all arguments have\nbeen processed, the slots that are still unfilled are filled with the\ncorresponding default value from the function definition. (Default\nvalues are calculated, once, when the function is defined; thus, a\nmutable object such as a list or dictionary used as default value will\nbe shared by all calls that don\'t specify an argument value for the\ncorresponding slot; this should usually be avoided.) If there are any\nunfilled slots for which no default value is specified, a\n``TypeError`` exception is raised. Otherwise, the list of filled\nslots is used as the argument list for the call.\n\nNote: An implementation may provide builtin functions whose positional\n parameters do not have names, even if they are \'named\' for the\n purpose of documentation, and which therefore cannot be supplied by\n keyword. In CPython, this is the case for functions implemented in\n C that use ``PyArg_ParseTuple`` to parse their arguments.\n\nIf there are more positional arguments than there are formal parameter\nslots, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``*identifier`` is present; in this case, that formal\nparameter receives a tuple containing the excess positional arguments\n(or an empty tuple if there were no excess positional arguments).\n\nIf any keyword argument does not correspond to a formal parameter\nname, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``**identifier`` is present; in this case, that\nformal parameter receives a dictionary containing the excess keyword\narguments (using the keywords as keys and the argument values as\ncorresponding values), or a (new) empty dictionary if there were no\nexcess keyword arguments.\n\nIf the syntax ``*expression`` appears in the function call,\n``expression`` must evaluate to a sequence. Elements from this\nsequence are treated as if they were additional positional arguments;\nif there are positional arguments *x1*,..., *xN*, and ``expression``\nevaluates to a sequence *y1*, ..., *yM*, this is equivalent to a call\nwith M+N positional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.\n\nA consequence of this is that although the ``*expression`` syntax may\nappear *after* some keyword arguments, it is processed *before* the\nkeyword arguments (and the ``**expression`` argument, if any -- see\nbelow). So:\n\n >>> def f(a, b):\n ... print(a, b)\n ...\n >>> f(b=1, *(2,))\n 2 1\n >>> f(a=1, *(2,))\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n TypeError: f() got multiple values for keyword argument \'a\'\n >>> f(1, *(2,))\n 1 2\n\nIt is unusual for both keyword arguments and the ``*expression``\nsyntax to be used in the same call, so in practice this confusion does\nnot arise.\n\nIf the syntax ``**expression`` appears in the function call,\n``expression`` must evaluate to a mapping, the contents of which are\ntreated as additional keyword arguments. In the case of a keyword\nappearing in both ``expression`` and as an explicit keyword argument,\na ``TypeError`` exception is raised.\n\nFormal parameters using the syntax ``*identifier`` or ``**identifier``\ncannot be used as positional argument slots or as keyword argument\nnames.\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', 'class': '\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [expression_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. It first evaluates the\ninheritance list, if present. Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing. The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.) When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary. The class name is bound to this class object in the\noriginal local namespace.\n\nClasses can also be decorated; as with functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``. Both class and\ninstance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results. Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n **PEP 3129** - Class Decorators\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions. The evaluation rules for the decorator\nexpressions are the same as for functions. The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n', 'comparisons': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects. The objects need not have the same type.\nIf both are numbers, they are converted to a common type. Otherwise,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes. You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n are identical to themselves, ``x is x`` but are not equal to\n themselves, ``x != x``. Additionally, comparing any value to a\n not-a-number value will return ``False``. For example, both ``3 <\n float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``cmp([1,2,x], [1,2,y])`` returns\n the same as ``cmp(x,y)``. If the corresponding element does not\n exist, the shorter sequence is ordered first (for example, ``[1,2] <\n [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if their sorted\n ``(key, value)`` lists compare equal. [4] Outcomes other than\n equality are resolved consistently, but are not otherwise defined.\n [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, ``min()``, ``max()``, and ``sorted()`` produce\n undefined results given a list of sets as inputs.\n\n* Most other objects of builtin types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison. Most\nnumberic types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is. When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``. This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons. For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership. ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise. ``x\nnot in s`` returns the negation of ``x in s``. All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` equivalent to ``any(x is e or x == e for val e\nin y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` and do\ndefine ``__getitem__()``, ``x in y`` is true if and only if there is a\nnon-negative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [6]\n', 'compound': '\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs. ``try`` specifies exception handlers and/or\ncleanup code for a group of statements, while the ``with`` statement\nallows the execution of initialization and finalization code around a\nblock of code. Function and class definitions are also syntactically\ncompound 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()`` calls 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 suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" 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 (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in 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``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\nWarning: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\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" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n N = None\n del N\n\nThat means that you have to assign the exception to a different name\nif you want to be able to refer to it after the except clause. The\nreason for this is that with the traceback attached to them,\nexceptions will form a reference cycle with the stack frame, keeping\nall locals in that frame alive until the next garbage collection\noccurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting\nof: ``exc_type``, the exception class; ``exc_value``, the exception\ninstance; ``exc_traceback``, a traceback object (see section *The\nstandard type hierarchy*) identifying the point in the program where\nthe exception occurred. ``sys.exc_info()`` values are restored to\ntheir previous values (before the call) when returning from a function\nthat handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost. The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" expression ["as" target] ":" suite\n\nThe execution of the ``with`` statement proceeds as follows:\n\n1. The context expression is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__enter__()`` method is invoked.\n\n3. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 5 below.\n\n4. The suite is executed.\n\n5. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Expression lists*. Note that the lambda form is\nmerely a shorthand for a simplified function definition; a function\ndefined in a "``def``" statement can be passed around or assigned to\nanother name just like a function defined by a lambda form. The\n"``def``" form is actually more powerful since it allows the execution\nof multiple statements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [expression_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. It first evaluates the\ninheritance list, if present. Each item in the inheritance list\nshould evaluate to a class object or class type which allows\nsubclassing. The class\'s suite is then executed in a new execution\nframe (see section *Naming and binding*), using a newly created local\nnamespace and the original global namespace. (Usually, the suite\ncontains only function definitions.) When the class\'s suite finishes\nexecution, its execution frame is discarded but its local namespace is\nsaved. [4] A class object is then created using the inheritance list\nfor the base classes and the saved local namespace for the attribute\ndictionary. The class name is bound to this class object in the\noriginal local namespace.\n\nClasses can also be decorated; as with functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass variables; they are shared by instances. Instance variables can\nbe set in a method with ``self.name = value``. Both class and\ninstance variables are accessible through the notation\n"``self.name``", and an instance variable hides a class variable with\nthe same name when accessed in this way. Class variables can be used\nas defaults for instance variables, but using mutable values there can\nlead to unexpected results. Descriptors can be used to create\ninstance variables with different implementation details.\n\nSee also:\n\n **PEP 3129** - Class Decorators\n\nClass definitions, like function definitions, may be wrapped by one or\nmore *decorator* expressions. The evaluation rules for the decorator\nexpressions are the same as for functions. The result must be a class\nobject, which is then bound to the class name.\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n', 'context-managers': '\nWith Statement Context Managers\n*******************************\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code. Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The ``with``\n statement will bind this method\'s return value to the target(s)\n specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be ``None``.\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that ``__exit__()`` methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n', 'continue': '\nThe ``continue`` statement\n**************************\n\n continue_stmt ::= "continue"\n\n``continue`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition or\n``finally`` clause within that loop. It continues with the next cycle\nof the nearest enclosing loop.\n\nWhen ``continue`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nstarting the next loop cycle.\n', 'conversions': '\nArithmetic conversions\n**********************\n\nWhen a description of an arithmetic operator below uses the phrase\n"the numeric arguments are converted to a common type," this means\nthat the operator implementation for built-in types works that way:\n\n* If either argument is a complex number, the other is converted to\n complex;\n\n* otherwise, if either argument is a floating point number, the other\n is converted to floating point;\n\n* otherwise, both must be integers and no conversion is necessary.\n\nSome additional rules apply for certain operators (e.g., a string left\nargument to the \'%\' operator). Extensions must define their own\nconversion behavior.\n', 'customization': '\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.last_traceback``. Circular references which are garbage are\n detected when the option cycle detector is enabled (it\'s on by\n default), but can only be cleaned up if there are no Python-\n level ``__del__()`` methods involved. Refer to the documentation\n 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 ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted. For this reason, ``__del__()`` methods should do\n the absolute minimum needed to maintain external invariants.\n Starting with version 1.5, Python guarantees that globals whose\n name begins with a single underscore are deleted from their\n module before other globals are deleted; if no other references\n to such globals exist, this may help in assuring that imported\n modules are still available at the time when the ``__del__()``\n method is called.\n\nobject.__repr__(self)\n\n Called by the ``repr()`` built-in function to compute the\n "official" string representation of an object. If at all possible,\n this should look like a valid Python expression that could be used\n to recreate an object with the same value (given an appropriate\n environment). If this is not possible, a string of the form\n ``<...some useful description...>`` should be returned. The return\n value must be a string object. If a class defines ``__repr__()``\n but not ``__str__()``, then ``__repr__()`` is also used when an\n "informal" string representation of instances of that class is\n 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 function to compute the "informal" string representation of an\n object. This differs from ``__repr__()`` in that it does not have\n to 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.__format__(self, format_spec)\n\n Called by the ``format()`` built-in function (and by extension, the\n ``format()`` method of class ``str``) to produce a "formatted"\n string representation of an object. The ``format_spec`` argument is\n a string that contains a description of the formatting options\n desired. The interpretation of the ``format_spec`` argument is up\n to the type implementing ``__format__()``, however most classes\n will either delegate formatting to one of the built-in types, or\n use a similar formatting option syntax.\n\n See *Format Specification Mini-Language* for a description of the\n standard formatting syntax.\n\n The return value must be a 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 These are the so-called "rich comparison" methods. The\n correspondence between operator symbols and method names is as\n follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n 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\n the paragraph on ``__hash__()`` for some important notes on\n creating *hashable* objects which support custom comparison\n operations and 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\n other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n reflection, and ``__eq__()`` and ``__ne__()`` are their own\n reflection.\n\n Arguments to rich comparison methods are never coerced.\n\nobject.__hash__(self)\n\n Called by built-in function ``hash()`` and for operations on\n members of hashed collections including ``set``, ``frozenset``, and\n ``dict``. ``__hash__()`` should return an integer. The only\n required property is that objects which compare equal have the same\n hash value; it is advised to somehow mix together (e.g. using\n exclusive or) the hash values for the components of the object that\n also play a part in comparison of objects.\n\n If a class does not define an ``__eq__()`` method it should not\n define a ``__hash__()`` operation either; if it defines\n ``__eq__()`` but not ``__hash__()``, its instances will not be\n usable as items in hashable collections. If a class defines\n mutable objects and implements an ``__eq__()`` method, it should\n not implement ``__hash__()``, since the implementation of hashable\n collections requires that a key\'s hash value is immutable (if the\n object\'s hash value changes, it will be in the wrong hash bucket).\n\n User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n by default; with them, all objects compare unequal (except with\n themselves) and ``x.__hash__()`` returns ``id(x)``.\n\n Classes which inherit a ``__hash__()`` method from a parent class\n but change the meaning of ``__eq__()`` such that the hash value\n returned is no longer appropriate (e.g. by switching to a value-\n based concept of equality instead of the default identity based\n equality) can explicitly flag themselves as being unhashable by\n setting ``__hash__ = None`` in the class definition. Doing so means\n that not only will instances of the class raise an appropriate\n ``TypeError`` when a program attempts to retrieve their hash value,\n but they will also be correctly identified as unhashable when\n checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n which define their own ``__hash__()`` to explicitly raise\n ``TypeError``).\n\n If a class that overrrides ``__eq__()`` needs to retain the\n implementation of ``__hash__()`` from a parent class, the\n interpreter must be told this explicitly by setting ``__hash__ =\n <ParentClass>.__hash__``. Otherwise the inheritance of\n ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n explicitly set to ``None``.\n\nobject.__bool__(self)\n\n Called to implement truth value testing, and the built-in operation\n ``bool()``; should return ``False`` or ``True``. When this method\n is not defined, ``__len__()`` is called, if it is defined (see\n below) and ``True`` is returned when the length is not zero. If a\n class defines neither ``__len__()`` nor ``__bool__()``, all its\n instances are considered true.\n', 'debugger': '\n``pdb`` --- The Python Debugger\n*******************************\n\nThe module ``pdb`` defines an interactive source code debugger for\nPython programs. It supports setting (conditional) breakpoints and\nsingle stepping at the source line level, inspection of stack frames,\nsource code listing, and evaluation of arbitrary Python code in the\ncontext of any stack frame. It also supports post-mortem debugging\nand can be called under program control.\n\nThe debugger is extensible --- it is actually defined as the class\n``Pdb``. This is currently undocumented but easily understood by\nreading the source. The extension interface uses the modules ``bdb``\n(undocumented) and ``cmd``.\n\nThe debugger\'s prompt is ``(Pdb)``. Typical usage to run a program\nunder control of the debugger is:\n\n >>> import pdb\n >>> import mymodule\n >>> pdb.run(\'mymodule.test()\')\n > <string>(0)?()\n (Pdb) continue\n > <string>(1)?()\n (Pdb) continue\n NameError: \'spam\'\n > <string>(1)?()\n (Pdb)\n\n``pdb.py`` can also be invoked as a script to debug other scripts.\nFor example:\n\n python -m pdb myscript.py\n\nWhen invoked as a script, pdb will automatically enter post-mortem\ndebugging if the program being debugged exits abnormally. After post-\nmortem debugging (or after normal exit of the program), pdb will\nrestart the program. Automatic restarting preserves pdb\'s state (such\nas breakpoints) and in most cases is more useful than quitting the\ndebugger upon program\'s exit.\n\nTypical usage to inspect a crashed program is:\n\n >>> import pdb\n >>> import mymodule\n >>> mymodule.test()\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n File "./mymodule.py", line 4, in test\n test2()\n File "./mymodule.py", line 3, in test2\n print(spam)\n NameError: spam\n >>> pdb.pm()\n > ./mymodule.py(3)test2()\n -> print(spam)\n (Pdb)\n\nThe module defines the following functions; each enters the debugger\nin a slightly different way:\n\npdb.run(statement[, globals[, locals]])\n\n Execute the *statement* (given as a string) under debugger control.\n The debugger prompt appears before any code is executed; you can\n set breakpoints and type ``continue``, or you can step through the\n statement using ``step`` or ``next`` (all these commands are\n explained below). The optional *globals* and *locals* arguments\n specify the environment in which the code is executed; by default\n the dictionary of the module ``__main__`` is used. (See the\n explanation of the built-in ``exec()`` or ``eval()`` functions.)\n\npdb.runeval(expression[, globals[, locals]])\n\n Evaluate the *expression* (given as a string) under debugger\n control. When ``runeval()`` returns, it returns the value of the\n expression. Otherwise this function is similar to ``run()``.\n\npdb.runcall(function[, argument, ...])\n\n Call the *function* (a function or method object, not a string)\n with the given arguments. When ``runcall()`` returns, it returns\n whatever the function call returned. The debugger prompt appears\n as soon as the function is entered.\n\npdb.set_trace()\n\n Enter the debugger at the calling stack frame. This is useful to\n hard-code a breakpoint at a given point in a program, even if the\n code is not otherwise being debugged (e.g. when an assertion\n fails).\n\npdb.post_mortem([traceback])\n\n Enter post-mortem debugging of the given *traceback* object. If no\n *traceback* is given, it uses the one of the exception that is\n currently being handled (an exception must be being handled if the\n default is to be used).\n\npdb.pm()\n\n Enter post-mortem debugging of the traceback found in\n ``sys.last_traceback``.\n', 'del': '\nThe ``del`` statement\n*********************\n\n del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather that spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block. If the name is unbound, a\n``NameError`` exception will be raised.\n\nIt is illegal to delete a name from the local namespace if it occurs\nas a free variable in a nested block.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n', 'dict': '\nDictionary displays\n*******************\n\nA dictionary display is a possibly empty series of key/datum pairs\nenclosed in curly braces:\n\n dict_display ::= "{" [key_datum_list | dict_comprehension] "}"\n key_datum_list ::= key_datum ("," key_datum)* [","]\n key_datum ::= expression ":" expression\n dict_comprehension ::= expression ":" expression comp_for\n\nA dictionary display yields a new dictionary object.\n\nIf a comma-separated sequence of key/datum pairs is given, they are\nevaluated from left to right to define the entries of the dictionary:\neach key object is used as a key into the dictionary to store the\ncorresponding datum. This means that you can specify the same key\nmultiple times in the key/datum list, and the final dictionary\'s value\nfor that key will be the last one given.\n\nA dict comprehension, in contrast to list and set comprehensions,\nneeds two expressions separated with a colon followed by the usual\n"for" and "if" clauses. When the comprehension is run, the resulting\nkey and value elements are inserted in the new dictionary in the order\nthey are produced.\n\nRestrictions on the types of the key values are listed earlier in\nsection *The standard type hierarchy*. (To summarize, the key type\nshould be *hashable*, which excludes all mutable objects.) Clashes\nbetween duplicate keys are not detected; the last datum (textually\nrightmost in the display) stored for a given key value prevails.\n', 'dynamic-features': '\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\nThe ``eval()`` and ``exec()`` functions do not have access to the full\nenvironment for resolving names. Names may be resolved in the local\nand global namespaces of the caller. Free variables are not resolved\nin the nearest enclosing namespace, but in the global namespace. [1]\nThe ``exec()`` and ``eval()`` functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n', 'else': '\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n', 'exceptions': '\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\nWarning: Exception messages are not part of the Python API. Their contents\n may change from one version of Python to the next without warning\n and should not be relied on by code which will run under multiple\n 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', 'execmodel': '\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 string argument passed\nto the built-in functions ``eval()`` and ``exec()`` 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,\nunless declared as ``nonlocal``. If a name is bound at the module\nlevel, it is a global variable. (The variables of the module code\nblock are local and global.) If a variable is used in a code block\nbut not defined there, it is a *free variable*.\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, or in\nthe second position of an ``except`` clause header. The ``import``\nstatement of the form "``from ...import *``" binds all names defined\nin the imported module, except those beginning with an underscore.\nThis form may only be used at the module 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\nname specified in the statement refer to the binding of that name in\nthe top-level namespace. Names are resolved in the top-level\nnamespace by searching the global namespace, i.e. the namespace of the\nmodule containing the code block, and the builtin namespace, the\nnamespace of the module ``builtins``. The global namespace is\nsearched first. If the name is not found there, the builtin namespace\nis searched. The global statement must precede all uses of the name.\n\nThe built-in 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``builtins``; when in any other module, ``__builtins__`` is an alias\nfor the dictionary of the ``builtins`` module itself.\n``__builtins__`` can be set to a user-created dictionary to create a\nweak form of restricted execution.\n\nNote: Users should not touch ``__builtins__``; it is strictly an\n implementation detail. Users wanting to override values in the\n built-in namespace should ``import`` the ``builtins`` module and\n modify its attributes appropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n``__main__``.\n\nThe global statement has the same scope as a name binding operation in\nthe same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\nInteraction with dynamic features\n---------------------------------\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- ``import *`` --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a ``SyntaxError``.\n\nThe ``eval()`` and ``exec()`` functions do not have access to the full\nenvironment for resolving names. Names may be resolved in the local\nand global namespaces of the caller. Free variables are not resolved\nin the nearest enclosing namespace, but in the global namespace. [1]\nThe ``exec()`` and ``eval()`` functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n\n\nExceptions\n==========\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the ``raise`` statement. Exception\nhandlers are specified with the ``try`` ... ``except`` statement. The\n``finally`` clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n``SystemExit``.\n\nExceptions are identified by class instances. The ``except`` clause\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\nWarning: Exception messages are not part of the Python API. Their contents\n may change from one version of Python to the next without warning\n and should not be relied on by code which will run under multiple\n 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', 'exprlists': '\nExpression lists\n****************\n\n expression_list ::= expression ( "," expression )* [","]\n\nAn expression list containing at least one comma yields a tuple. The\nlength of the tuple is the number of expressions in the list. The\nexpressions are evaluated from left to right.\n\nThe trailing comma is required only to create a single tuple (a.k.a. a\n*singleton*); it is optional in all other cases. A single expression\nwithout a trailing comma doesn\'t create a tuple, but rather yields the\nvalue of that expression. (To create an empty tuple, use an empty pair\nof parentheses: ``()``.)\n', 'floating': '\nFloating point literals\n***********************\n\nFloating point literals are described by the following lexical\ndefinitions:\n\n floatnumber ::= pointfloat | exponentfloat\n pointfloat ::= [intpart] fraction | intpart "."\n exponentfloat ::= (intpart | pointfloat) exponent\n intpart ::= digit+\n fraction ::= "." digit+\n exponent ::= ("e" | "E") ["+" | "-"] digit+\n\nNote that the integer and exponent parts are always interpreted using\nradix 10. For example, ``077e010`` is legal, and denotes the same\nnumber as ``77e10``. The allowed range of floating point literals is\nimplementation-dependent. Some examples of floating point literals:\n\n 3.14 10. .001 1e100 3.14e-10 0e0\n\nNote that numeric literals do not include a sign; a phrase like ``-1``\nis actually an expression composed of the unary operator ``-`` and the\nliteral ``1``.\n', 'for': '\nThe ``for`` statement\n*********************\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in 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``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.\n\nWarning: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\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', 'formatstrings': '\nFormat String Syntax\n********************\n\nThe ``str.format()`` method and the ``Formatter`` class share the same\nsyntax for format strings (although in the case of ``Formatter``,\nsubclasses can define their own format string syntax.)\n\nFormat strings contain "replacement fields" surrounded by curly braces\n``{}``. Anything that is not contained in braces is considered literal\ntext, which is copied unchanged to the output. If you need to include\na brace character in the literal text, it can be escaped by doubling:\n``{{`` and ``}}``.\n\nThe grammar for a replacement field is as follows:\n\n replacement_field ::= "{" field_name ["!" conversion] [":" format_spec] "}"\n field_name ::= (identifier | integer) ("." attribute_name | "[" element_index "]")*\n attribute_name ::= identifier\n element_index ::= integer\n conversion ::= "r" | "s" | "a"\n format_spec ::= <described in the next section>\n\nIn less formal terms, the replacement field starts with a\n*field_name*, which can either be a number (for a positional\nargument), or an identifier (for keyword arguments). Following this\nis an optional *conversion* field, which is preceded by an exclamation\npoint ``\'!\'``, and a *format_spec*, which is preceded by a colon\n``\':\'``.\n\nThe *field_name* itself begins with either a number or a keyword. If\nit\'s a number, it refers to a positional argument, and if it\'s a\nkeyword it refers to a named keyword argument. This can be followed\nby any number of index or attribute expressions. An expression of the\nform ``\'.name\'`` selects the named attribute using ``getattr()``,\nwhile an expression of the form ``\'[index]\'`` does an index lookup\nusing ``__getitem__()``.\n\nSome simple format string examples:\n\n "First, thou shalt count to {0}" # References first positional argument\n "My quest is {name}" # References keyword argument \'name\'\n "Weight in tons {0.weight}" # \'weight\' attribute of first positional arg\n "Units destroyed: {players[0]}" # First element of keyword argument \'players\'.\n\nThe *conversion* field causes a type coercion before formatting.\nNormally, the job of formatting a value is done by the\n``__format__()`` method of the value itself. However, in some cases\nit is desirable to force a type to be formatted as a string,\noverriding its own definition of formatting. By converting the value\nto a string before calling ``__format__()``, the normal formatting\nlogic is bypassed.\n\nThree conversion flags are currently supported: ``\'!s\'`` which calls\n``str()`` on the value, ``\'!r\'`` which calls ``repr()`` and ``\'!a\'``\nwhich calls ``ascii()``.\n\nSome examples:\n\n "Harold\'s a clever {0!s}" # Calls str() on the argument first\n "Bring out the holy {name!r}" # Calls repr() on the argument first\n\nThe *format_spec* field contains a specification of how the value\nshould be presented, including such details as field width, alignment,\npadding, decimal precision and so on. Each value type can define it\'s\nown "formatting mini-language" or interpretation of the *format_spec*.\n\nMost built-in types support a common formatting mini-language, which\nis described in the next section.\n\nA *format_spec* field can also include nested replacement fields\nwithin it. These nested replacement fields can contain only a field\nname; conversion flags and format specifications are not allowed. The\nreplacement fields within the format_spec are substituted before the\n*format_spec* string is interpreted. This allows the formatting of a\nvalue to be dynamically specified.\n\nFor example, suppose you wanted to have a replacement field whose\nfield width is determined by another variable:\n\n "A man with two {0:{1}}".format("noses", 10)\n\nThis would first evaluate the inner replacement field, making the\nformat string effectively:\n\n "A man with two {0:10}"\n\nThen the outer replacement field would be evaluated, producing:\n\n "noses "\n\nWhich is substituted into the string, yielding:\n\n "A man with two noses "\n\n(The extra space is because we specified a field width of 10, and\nbecause left alignment is the default for strings.)\n\n\nFormat Specification Mini-Language\n==================================\n\n"Format specifications" are used within replacement fields contained\nwithin a format string to define how individual values are presented\n(see *Format String Syntax*.) They can also be passed directly to the\nbuiltin ``format()`` function. Each formattable type may define how\nthe format specification is to be interpreted.\n\nMost built-in types implement the following options for format\nspecifications, although some of the formatting options are only\nsupported by the numeric types.\n\nA general convention is that an empty format string (``""``) produces\nthe same result as if you had called ``str()`` on the value.\n\nThe general form of a *standard format specifier* is:\n\n format_spec ::= [[fill]align][sign][#][0][width][.precision][type]\n fill ::= <a character other than \'}\'>\n align ::= "<" | ">" | "=" | "^"\n sign ::= "+" | "-" | " "\n width ::= integer\n precision ::= integer\n type ::= "b" | "c" | "d" | "e" | "E" | "f" | "F" | "g" | "G" | "n" | "o" | "x" | "X" | "%"\n\nThe *fill* character can be any character other than \'}\' (which\nsignifies the end of the field). The presence of a fill character is\nsignaled by the *next* character, which must be one of the alignment\noptions. If the second character of *format_spec* is not a valid\nalignment option, then it is assumed that both the fill character and\nthe alignment option are absent.\n\nThe meaning of the various alignment options is as follows:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'<\'`` | Forces the field to be left-aligned within the available |\n | | space (This is the default.) |\n +-----------+------------------------------------------------------------+\n | ``\'>\'`` | Forces the field to be right-aligned within the available |\n | | space. |\n +-----------+------------------------------------------------------------+\n | ``\'=\'`` | Forces the padding to be placed after the sign (if any) |\n | | but before the digits. This is used for printing fields |\n | | in the form \'+000000120\'. This alignment option is only |\n | | valid for numeric types. |\n +-----------+------------------------------------------------------------+\n | ``\'^\'`` | Forces the field to be centered within the available |\n | | space. |\n +-----------+------------------------------------------------------------+\n\nNote that unless a minimum field width is defined, the field width\nwill always be the same size as the data to fill it, so that the\nalignment option has no meaning in this case.\n\nThe *sign* option is only valid for number types, and can be one of\nthe following:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'+\'`` | indicates that a sign should be used for both positive as |\n | | well as negative numbers. |\n +-----------+------------------------------------------------------------+\n | ``\'-\'`` | indicates that a sign should be used only for negative |\n | | numbers (this is the default behavior). |\n +-----------+------------------------------------------------------------+\n | space | indicates that a leading space should be used on positive |\n | | numbers, and a minus sign on negative numbers. |\n +-----------+------------------------------------------------------------+\n\nThe ``\'#\'`` option is only valid for integers, and only for binary,\noctal, or hexadecimal output. If present, it specifies that the\noutput will be prefixed by ``\'0b\'``, ``\'0o\'``, or ``\'0x\'``,\nrespectively.\n\n*width* is a decimal integer defining the minimum field width. If not\nspecified, then the field width will be determined by the content.\n\nIf the *width* field is preceded by a zero (``\'0\'``) character, this\nenables zero-padding. This is equivalent to an *alignment* type of\n``\'=\'`` and a *fill* character of ``\'0\'``.\n\nThe *precision* is a decimal number indicating how many digits should\nbe displayed after the decimal point for a floating point value\nformatted with ``\'f\'`` and ``\'F\'``, or before and after the decimal\npoint for a floating point value formatted with ``\'g\'`` or ``\'G\'``.\nFor non-number types the field indicates the maximum field size - in\nother words, how many characters will be used from the field content.\nThe *precision* is ignored for integer values.\n\nFinally, the *type* determines how the data should be presented.\n\nThe available integer presentation types are:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'b\'`` | Binary format. Outputs the number in base 2. |\n +-----------+------------------------------------------------------------+\n | ``\'c\'`` | Character. Converts the integer to the corresponding |\n | | unicode character before printing. |\n +-----------+------------------------------------------------------------+\n | ``\'d\'`` | Decimal Integer. Outputs the number in base 10. |\n +-----------+------------------------------------------------------------+\n | ``\'o\'`` | Octal format. Outputs the number in base 8. |\n +-----------+------------------------------------------------------------+\n | ``\'x\'`` | Hex format. Outputs the number in base 16, using lower- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'X\'`` | Hex format. Outputs the number in base 16, using upper- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'d\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'d\'``. |\n +-----------+------------------------------------------------------------+\n\nThe available presentation types for floating point and decimal values\nare:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'e\'`` | Exponent notation. Prints the number in scientific |\n | | notation using the letter \'e\' to indicate the exponent. |\n +-----------+------------------------------------------------------------+\n | ``\'E\'`` | Exponent notation. Same as ``\'e\'`` except it uses an upper |\n | | case \'E\' as the separator character. |\n +-----------+------------------------------------------------------------+\n | ``\'f\'`` | Fixed point. Displays the number as a fixed-point number. |\n +-----------+------------------------------------------------------------+\n | ``\'F\'`` | Fixed point. Same as ``\'f\'``. |\n +-----------+------------------------------------------------------------+\n | ``\'g\'`` | General format. This prints the number as a fixed-point |\n | | number, unless the number is too large, in which case it |\n | | switches to ``\'e\'`` exponent notation. Infinity and NaN |\n | | values are formatted as ``inf``, ``-inf`` and ``nan``, |\n | | respectively. |\n +-----------+------------------------------------------------------------+\n | ``\'G\'`` | General format. Same as ``\'g\'`` except switches to ``\'E\'`` |\n | | if the number gets to large. The representations of |\n | | infinity and NaN are uppercased, too. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'g\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | ``\'%\'`` | Percentage. Multiplies the number by 100 and displays in |\n | | fixed (``\'f\'``) format, followed by a percent sign. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'g\'``. |\n +-----------+------------------------------------------------------------+\n', 'function': '\nFunction definitions\n********************\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Expression lists*. Note that the lambda form is\nmerely a shorthand for a simplified function definition; a function\ndefined in a "``def``" statement can be passed around or assigned to\nanother name just like a function defined by a lambda form. The\n"``def``" form is actually more powerful since it allows the execution\nof multiple statements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n', 'global': '\nThe ``global`` statement\n************************\n\n global_stmt ::= "global" identifier ("," identifier)*\n\nThe ``global`` statement is a declaration which holds for the entire\ncurrent code block. It means that the listed identifiers are to be\ninterpreted as globals. It would be impossible to assign to a global\nvariable without ``global``, although free variables may refer to\nglobals without being declared global.\n\nNames listed in a ``global`` statement must not be used in the same\ncode block textually preceding that ``global`` statement.\n\nNames listed in a ``global`` statement must not be defined as formal\nparameters or in a ``for`` loop control target, ``class`` definition,\nfunction definition, or ``import`` statement.\n\n(The current implementation does not enforce the latter two\nrestrictions, but programs should not abuse this freedom, as future\nimplementations may enforce them or silently change the meaning of the\nprogram.)\n\n**Programmer\'s note:** the ``global`` is a directive to the parser.\nIt applies only to code parsed at the same time as the ``global``\nstatement. In particular, a ``global`` statement contained in a string\nor code object supplied to the builtin ``exec()`` function does not\naffect the code block *containing* the function call, and code\ncontained in such a string is unaffected by ``global`` statements in\nthe code containing the function call. The same applies to the\n``eval()`` and ``compile()`` functions.\n', 'id-classes': '\nReserved classes of identifiers\n*******************************\n\nCertain classes of identifiers (besides keywords) have special\nmeanings. These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n Not imported by ``from module import *``. The special identifier\n ``_`` is used in the interactive interpreter to store the result of\n the last evaluation; it is stored in the ``builtins`` 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);\n applications should not expect to define additional names using\n this convention. The set of names of this class defined by Python\n may be extended in future versions. See section *Special method\n names*.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n', 'identifiers': '\nIdentifiers and keywords\n************************\n\nIdentifiers (also referred to as *names*) are described by the\nfollowing lexical definitions.\n\nThe syntax of identifiers in Python is based on the Unicode standard\nannex UAX-31, with elaboration and changes as defined below; see also\n**PEP 3131** for further details.\n\nWithin the ASCII range (U+0001..U+007F), the valid characters for\nidentifiers are the same as in Python 2.x: the uppercase and lowercase\nletters ``A`` through ``Z``, the underscore ``_`` and, except for the\nfirst character, the digits ``0`` through ``9``.\n\nPython 3.0 introduces additional characters from outside the ASCII\nrange (see **PEP 3131**). For these characters, the classification\nuses the version of the Unicode Character Database as included in the\n``unicodedata`` module.\n\nIdentifiers are unlimited in length. Case is significant.\n\n identifier ::= id_start id_continue*\n id_start ::= <all characters in general categories Lu, Ll, Lt, Lm, Lo, Nl, the underscore, and characters with the Other_ID_Start property>\n id_continue ::= <all characters in id_start, plus characters in the categories Mn, Mc, Nd, Pc and others with the Other_ID_Continue property>\n\nThe Unicode category codes mentioned above stand for:\n\n* *Lu* - uppercase letters\n\n* *Ll* - lowercase letters\n\n* *Lt* - titlecase letters\n\n* *Lm* - modifier letters\n\n* *Lo* - other letters\n\n* *Nl* - letter numbers\n\n* *Mn* - nonspacing marks\n\n* *Mc* - spacing combining marks\n\n* *Nd* - decimal numbers\n\n* *Pc* - connector punctuations\n\nAll identifiers are converted into the normal form NFC while parsing;\ncomparison of identifiers is based on NFC.\n\nA non-normative HTML file listing all valid identifier characters for\nUnicode 4.1 can be found at http://www.dcl.hpi.uni-\npotsdam.de/home/loewis/table-3131.html.\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 False class finally is return\n None continue for lambda try\n True def from nonlocal while\n and del global not with\n as elif if or yield\n assert else import pass\n break except in raise\n\n\nReserved classes of identifiers\n===============================\n\nCertain classes of identifiers (besides keywords) have special\nmeanings. These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n Not imported by ``from module import *``. The special identifier\n ``_`` is used in the interactive interpreter to store the result of\n the last evaluation; it is stored in the ``builtins`` 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);\n applications should not expect to define additional names using\n this convention. The set of names of this class defined by Python\n may be extended in future versions. See section *Special method\n names*.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n', 'if': '\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n', 'imaginary': '\nImaginary literals\n******************\n\nImaginary literals are described by the following lexical definitions:\n\n imagnumber ::= (floatnumber | intpart) ("j" | "J")\n\nAn imaginary literal yields a complex number with a real part of 0.0.\nComplex numbers are represented as a pair of floating point numbers\nand have the same restrictions on their range. To create a complex\nnumber with a nonzero real part, add a floating point number to it,\ne.g., ``(3+4j)``. Some examples of imaginary literals:\n\n 3.14j 10.j 10j .001j 1e100j 3.14e-10j\n', 'import': '\nThe ``import`` statement\n************************\n\n import_stmt ::= "import" module ["as" name] ( "," module ["as" name] )*\n | "from" relative_module "import" identifier ["as" name]\n ( "," identifier ["as" name] )*\n | "from" relative_module "import" "(" identifier ["as" name]\n ( "," identifier ["as" name] )* [","] ")"\n | "from" module "import" "*"\n module ::= (identifier ".")* identifier\n relative_module ::= "."* module | "."+\n name ::= identifier\n\nImport statements are executed in two steps: (1) find a module, and\ninitialize it if necessary; (2) define a name or names in the local\nnamespace (of the scope where the ``import`` statement occurs). The\nfirst form (without ``from``) repeats these steps for each identifier\nin the list. The form with ``from`` performs step (1) once, and then\nperforms step (2) repeatedly.\n\nIn this context, to "initialize" a built-in or extension module means\nto call an initialization function that the module must provide for\nthe purpose (in the reference implementation, the function\'s name is\nobtained by prepending string "init" to the module\'s name); to\n"initialize" a Python-coded module means to execute the module\'s body.\n\nThe system maintains a table of modules that have been or are being\ninitialized, indexed by module name. This table is accessible as\n``sys.modules``. When a module name is found in this table, step (1)\nis finished. If not, a search for a module definition is started.\nWhen a module is found, it is loaded. Details of the module searching\nand loading process are implementation and platform specific. It\ngenerally involves searching for a "built-in" module with the given\nname and then searching a list of locations given as ``sys.path``.\n\nIf a built-in module is found, its built-in initialization code is\nexecuted and step (1) is finished. If no matching file is found,\n``ImportError`` is raised. If a file is found, it is parsed, yielding\nan executable code block. If a syntax error occurs, ``SyntaxError``\nis raised. Otherwise, an empty module of the given name is created\nand inserted in the module table, and then the code block is executed\nin the context of this module. Exceptions during this execution\nterminate step (1).\n\nWhen step (1) finishes without raising an exception, step (2) can\nbegin.\n\nThe first form of ``import`` statement binds the module name in the\nlocal namespace to the module object, and then goes on to import the\nnext identifier, if any. If the module name is followed by ``as``,\nthe name following ``as`` is used as the local name for the module.\n\nThe ``from`` form does not bind the module name: it goes through the\nlist of identifiers, looks each one of them up in the module found in\nstep (1), and binds the name in the local namespace to the object thus\nfound. As with the first form of ``import``, an alternate local name\ncan be supplied by specifying "``as`` localname". If a name is not\nfound, ``ImportError`` is raised. If the list of identifiers is\nreplaced by a star (``\'*\'``), all public names defined in the module\nare bound in the local namespace of the ``import`` statement..\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named ``__all__``; if defined, it\nmust be a sequence of strings which are names defined or imported by\nthat module. The names given in ``__all__`` are all considered public\nand are required to exist. If ``__all__`` is not defined, the set of\npublic names includes all names found in the module\'s namespace which\ndo not begin with an underscore character (``\'_\'``). ``__all__``\nshould contain the entire public API. It is intended to avoid\naccidentally exporting items that are not part of the API (such as\nlibrary modules which were imported and used within the module).\n\nThe ``from`` form with ``*`` may only occur in a module scope. If the\nwild card form of import --- ``import *`` --- is used in a function\nand the function contains or is a nested block with free variables,\nthe compiler will raise a ``SyntaxError``.\n\n**Hierarchical module names:** when the module names contains one or\nmore dots, the module search path is carried out differently. The\nsequence of identifiers up to the last dot is used to find a\n"package"; the final identifier is then searched inside the package.\nA package is generally a subdirectory of a directory on ``sys.path``\nthat has a file ``__init__.py``.\n\nThe built-in function ``__import__()`` is provided to support\napplications that determine which modules need to be loaded\ndynamically; refer to *Built-in Functions* for additional information.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python. The future\nstatement is intended to ease migration to future versions of Python\nthat introduce incompatible changes to the language. It allows use of\nthe new features on a per-module basis before the release in which the\nfeature becomes standard.\n\n future_statement ::= "from" "__future__" "import" feature ["as" name]\n ("," feature ["as" name])*\n | "from" "__future__" "import" "(" feature ["as" name]\n ("," feature ["as" name])* [","] ")"\n feature ::= identifier\n name ::= identifier\n\nA future statement must appear near the top of the module. The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 3.0 are ``absolute_import``,\n``division``, ``generators``, ``unicode_literals``,\n``print_function``, ``nested_scopes`` and ``with_statement``. They\nare all redundant because they are always enabled, and only kept for\nbackwards compatibility.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code. It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently. Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module ``__future__``, described later, and it\nwill be imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by calls to the builtin functions ``exec()`` and\n``compile()`` that occur in a module ``M`` containing a future\nstatement will, by default, use the new syntax or semantics associated\nwith the future statement. This can be controlled by optional\narguments to ``compile()`` --- see the documentation of that function\nfor details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session. If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n', 'in': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects. The objects need not have the same type.\nIf both are numbers, they are converted to a common type. Otherwise,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes. You can control comparison behavior of objects of non-builtin\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n are identical to themselves, ``x is x`` but are not equal to\n themselves, ``x != x``. Additionally, comparing any value to a\n not-a-number value will return ``False``. For example, both ``3 <\n float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``cmp([1,2,x], [1,2,y])`` returns\n the same as ``cmp(x,y)``. If the corresponding element does not\n exist, the shorter sequence is ordered first (for example, ``[1,2] <\n [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if their sorted\n ``(key, value)`` lists compare equal. [4] Outcomes other than\n equality are resolved consistently, but are not otherwise defined.\n [5]\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, ``min()``, ``max()``, and ``sorted()`` produce\n undefined results given a list of sets as inputs.\n\n* Most other objects of builtin types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison. Most\nnumberic types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is. When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``. This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons. For example, ``Decimal(2) ==\n2`` and *2 == float(2)`* but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership. ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise. ``x\nnot in s`` returns the negation of ``x in s``. All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` equivalent to ``any(x is e or x == e for val e\nin y)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` and do\ndefine ``__getitem__()``, ``x in y`` is true if and only if there is a\nnon-negative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [6]\n', 'integers': '\nInteger literals\n****************\n\nInteger literals are described by the following lexical definitions:\n\n integer ::= decimalinteger | octinteger | hexinteger | bininteger\n decimalinteger ::= nonzerodigit digit* | "0"+\n nonzerodigit ::= "1"..."9"\n digit ::= "0"..."9"\n octinteger ::= "0" ("o" | "O") octdigit+\n hexinteger ::= "0" ("x" | "X") hexdigit+\n bininteger ::= "0" ("b" | "B") bindigit+\n octdigit ::= "0"..."7"\n hexdigit ::= digit | "a"..."f" | "A"..."F"\n bindigit ::= "0" | "1"\n\nThere is no limit for the length of integer literals apart from what\ncan be stored in available memory.\n\nNote that leading zeros in a non-zero decimal number are not allowed.\nThis is for disambiguation with C-style octal literals, which Python\nused before version 3.0.\n\nSome examples of integer literals:\n\n 7 2147483647 0o177 0b100110111\n 3 79228162514264337593543950336 0o377 0x100000000\n 79228162514264337593543950336 0xdeadbeef\n', 'lambda': '\nExpression lists\n****************\n\n expression_list ::= expression ( "," expression )* [","]\n\nAn expression list containing at least one comma yields a tuple. The\nlength of the tuple is the number of expressions in the list. The\nexpressions are evaluated from left to right.\n\nThe trailing comma is required only to create a single tuple (a.k.a. a\n*singleton*); it is optional in all other cases. A single expression\nwithout a trailing comma doesn\'t create a tuple, but rather yields the\nvalue of that expression. (To create an empty tuple, use an empty pair\nof parentheses: ``()``.)\n', 'lists': '\nList displays\n*************\n\nA list display is a possibly empty series of expressions enclosed in\nsquare brackets:\n\n list_display ::= "[" [expression_list | comprehension] "]"\n\nA list display yields a new list object, the contents being specified\nby either a list of expressions or a comprehension. When a comma-\nseparated list of expressions is supplied, its elements are evaluated\nfrom left to right and placed into the list object in that order.\nWhen a comprehension is supplied, the list is constructed from the\nelements resulting from the comprehension.\n', 'naming': '\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 string argument passed\nto the built-in functions ``eval()`` and ``exec()`` 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,\nunless declared as ``nonlocal``. If a name is bound at the module\nlevel, it is a global variable. (The variables of the module code\nblock are local and global.) If a variable is used in a code block\nbut not defined there, it is a *free variable*.\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, or in\nthe second position of an ``except`` clause header. The ``import``\nstatement of the form "``from ...import *``" binds all names defined\nin the imported module, except those beginning with an underscore.\nThis form may only be used at the module 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\nname specified in the statement refer to the binding of that name in\nthe top-level namespace. Names are resolved in the top-level\nnamespace by searching the global namespace, i.e. the namespace of the\nmodule containing the code block, and the builtin namespace, the\nnamespace of the module ``builtins``. The global namespace is\nsearched first. If the name is not found there, the builtin namespace\nis searched. The global statement must precede all uses of the name.\n\nThe built-in 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``builtins``; when in any other module, ``__builtins__`` is an alias\nfor the dictionary of the ``builtins`` module itself.\n``__builtins__`` can be set to a user-created dictionary to create a\nweak form of restricted execution.\n\nNote: Users should not touch ``__builtins__``; it is strictly an\n implementation detail. Users wanting to override values in the\n built-in namespace should ``import`` the ``builtins`` module and\n modify its attributes appropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n``__main__``.\n\nThe global statement has the same scope as a name binding operation in\nthe same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\nInteraction with dynamic features\n=================================\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- ``import *`` --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a ``SyntaxError``.\n\nThe ``eval()`` and ``exec()`` functions do not have access to the full\nenvironment for resolving names. Names may be resolved in the local\nand global namespaces of the caller. Free variables are not resolved\nin the nearest enclosing namespace, but in the global namespace. [1]\nThe ``exec()`` and ``eval()`` functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n', 'numbers': "\nNumeric literals\n****************\n\nThere are three types of numeric literals: integers, floating point\nnumbers, and imaginary numbers. There are no complex literals\n(complex numbers can be formed by adding a real number and an\nimaginary number).\n\nNote that numeric literals do not include a sign; a phrase like ``-1``\nis actually an expression composed of the unary operator '``-``' and\nthe literal ``1``.\n", 'numeric-types': "\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.__truediv__(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 (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n ``|``). For instance, to evaluate the expression ``x + y``, where\n *x* is an 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__()``. Note that\n ``__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.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(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 (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n ``|``) with reflected (swapped) operands. These functions are only\n called if the left operand does not support the corresponding\n operation and the operands are of different types. [3] For\n instance, to evaluate the expression ``x - y``, where *y* is an\n instance of a class that has an ``__rsub__()`` method,\n ``y.__rsub__(x)`` is called if ``x.__sub__(y)`` returns\n *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.__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 operations (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\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 operation falls back to the normal methods. For instance, to\n evaluate the expression ``x += y``, where *x* is an instance of a\n class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n called. If *x* is an instance of a class that does not define a\n ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n Called to implement the unary arithmetic operations (``-``, ``+``,\n ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__float__(self)\nobject.__round__(self[, n])\n\n Called to implement the built-in functions ``complex()``,\n ``int()``, ``float()`` and ``round()``. Should return a value of\n the appropriate type.\n\nobject.__index__(self)\n\n Called to implement ``operator.index()``. Also called whenever\n Python needs an integer object (such as in slicing, or in the\n built-in ``bin()``, ``hex()`` and ``oct()`` functions). Must return\n an integer.\n",


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