BIfunctions.txt

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kevinDB
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120429
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BIfunctions.txt
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2011-12-03 14:19:20
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Python Built Functions
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Python Built-in Functions from http://docs.python.org/library/functions.html
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  1. abs(x)
    • Return the absolute value of a number.
    • The argument may be a plain or long integer or a floating point number.
  2. all(iterable)
    Return True if all elements of the *iterable* are true (or if the iterable is empty).
  3. any(iterable)
    Return True if any element of the *iterable* is true. If the iterable is empty, return False.
  4. basestring()
    • This abstract type is the superclass for ``str`` and ``unicode``.
    • It cannot be called or instantiated, but it can be used to test whether an object is an instance of ``str`` or ``unicode``.
    • ``isinstance(obj, basestring)`` is equivalent to ``isinstance(obj,(str, unicode))``.
  5. bin(x)
    • Convert an integer number to a binary string. The result is a valid Python expression.
    • If *x* is not a Python ``int`` object, it has to define an ``__index__()`` method that returns an integer.
  6. bool([x])
    • Convert a value to a Boolean, using the standard truth testing procedure.
    • If *x* is false or omitted, this returns ``False``; otherwise it returns ``True``.
    • ``bool`` is also a class, which is a subclass of ``int``.
    • Class ``bool`` cannot be subclassed further.
    • Its only instances are ``False`` and ``True``.
  7. bytearray([source[, encoding[, errors]]])
    • Return a new array of bytes. The ``bytearray`` type is a mutable sequence of integers in the range 0 <= x < 256.
    • It has most of the usual methods of mutable sequences, described in *Mutable Sequence Types*, as well as most methods that the ``str`` type has, see *String Methods*.
    • The optional *source* parameter can be used to initialize the array in a few different ways:
    • 1: If it is a *string*, you must also give the *encoding* (and optionally, *errors*) parameters; ``bytearray()`` then converts the string to bytes using ``str.encode()``.
    • 2: If it is an *integer*, the array will have that size and will be initialized with null bytes.
    • 3: If it is an object conforming to the *buffer* interface, a read-only buffer of the object will be used to initialize the bytes array.
    • 4: If it is an *iterable*, it must be an iterable of integers in the range ``0 <= x < 256``, which are used as the initial contents of the array.
    • Note: Without an argument, an array of size 0 is created.
  8. callable(object)
    • Return ``True`` if the *object* argument appears callable, ``False`` if not.
    • If this returns true, it is still possible that a call fails, but if it is false, calling *object* will never succeed.
    • Note that classes are callable (calling a class returns a new instance);
    • class instances are callable if they have a ``__call__()`` method.
  9. chr(i)
    • Return a string of one character whose ASCII code is the integer *i*.
    • For example, ``chr(97)`` returns the string ``'a'``. This is the inverse of ``ord()``.
    • The argument must be in the range [0..255], inclusive;
    • ``ValueError`` will be raised if *i* is outside that range. See also ``unichr()``.
  10. classmethod(function)
    • Return a class method for *function*.
    • A class method receives the class as implicit first argument, just like an instance method receives the instance.
    • To declare a class method, use this idiom:
    • class C:
    • @classmethod
    • def f(cls, arg1, arg2, ...): ...
    • The ``@classmethod`` form is a function *decorator* -- see the description of function definitions in *Function definitions* for details.
    • It can be called either on the class (such as ``C.f()``) or on an instance (such as ``C().f()``).
    • The instance is ignored except for its class.
    • If a class method is called for a derived class, the derived class object is passed as the implied first argument.
    • Class methods are different than C++ or Java static methods. If you want those, see ``staticmethod()`` in this section.
    • For more information on class methods, consult the documentation on the standard type hierarchy in *The standard type hierarchy*.
  11. cmp(x, y)
    • Compare the two objects *x* and *y* and return an integer according to the outcome.
    • The return value is negative if ``x < y``, zero if ``x == y`` and strictly positive if ``x > y``.
  12. compile(source, filename, mode[, flags[, dont_inherit]])
    • Compile the *source* into a code or AST object.
    • Code objects can be executed by an ``exec`` statement or evaluated by a call tom``eval()``.
    • *source* can either be a string or an AST object.
    • Refer to the ``ast`` module documentation for information on how to work with AST objects.
    • Argument 1: The *filename* argument should give the file from which the code was read; pass some recognizable value if it wasn't read from a file (``''`` is commonly used).
    • Argument 2: The *mode* argument specifies what kind of code must be compiled; it can be ``'exec'`` if *source* consists of a sequence of statements, ``'eval'`` if it consists of a single expression, or ``'single'`` if it consists of a single interactive statement (in the latter case, expression statements that evaluate to something other than ``None`` will be printed).
    • Argument 3: The optional arguments *flags* and *dont_inherit* control which future statements (see **PEP 236**) affect the compilation of *source*. If neither is present (or both are zero) the code is compiled with those future statements that are in effect in the code that is calling compile. If the *flags* argument is given and *dont_inherit* is not (or is zero) then the future statements specified by the *flags* argument are used in addition to those that would be used anyway. If *dont_inherit* is a non-zero integer then the *flags* argument is it -- the future statements in effect around the call to compile are ignored.
    • Future statements are specified by bits which can be bitwise ORed together to specify multiple statements. The bitfield required to specify a given feature can be found as the ``compiler_flag`` attribute on the ``_Feature`` instance in the ``__future__`` module.
    • This function raises ``SyntaxError`` if the compiled source is invalid, and ``TypeError`` if the source contains null bytes.
    • Note: When compiling a string with multi-line code in ``'single'`` or ``'eval'`` mode, input must be terminated by at least one newline character. This is to facilitate detection of incomplete and complete statements in the ``code`` module.
  13. complex([real[, imag]])
    • Create a complex number with the value *real* + *imag**j or convert a string or number to a complex number.
    • If the first parameter is a string, it will be interpreted as a complex number and the function must be called without a second parameter.
    • The second parameter can never be a string. Each argument may be any numeric type (including complex).
    • If *imag* is omitted, it defaults to zero and the function serves as a numeric conversion function like ``int()``, ``long()`` and ``float()``.
    • If both arguments are omitted, returns ``0j``.
  14. delattr(object, name)
    • The function deletes the named attribute, provided the object allows it.
    • This is a relative of ``setattr()``. The arguments are an object and a string.
    • The string must be the name of one of the object's attributes.
    • For example, ``delattr(x, 'foobar')`` is equivalent to ``del x.foobar``.
  15. dict([arg])
    • Create a new data dictionary, optionally with items taken from *arg*.
    • The dictionary type is described in *Mapping Types --- dict*.
  16. dir([object])
    • Without arguments, return the list of names in the current local scope.
    • With an argument, attempt to return a list of valid attributes for that object.
    • If the object has a method named ``__dir__()``, this method will be called and must return the list of attributes. This allows objects that implement a custom ``__getattr__()`` or ``__getattribute__()`` function to customize the way ``dir()`` reports their attributes.
    • If the object does not provide ``__dir__()``, the function tries its best to gather information from the object's ``__dict__`` attribute, if defined, and from its type object. The resulting list is not necessarily complete, and may be inaccurate when the object has a custom ``__getattr__()``.
    • The default ``dir()`` mechanism behaves differently with different types of objects, as it attempts to produce the most relevant, rather than complete, information:
    • 1. If the object is a module object, the list contains the names of the module's attributes.
    • 2. If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases.
    • 3. Otherwise, the list contains the object's attributes' names, the names of its class's attributes, and recursively of the attributes of its class's base classes.
  17. divmod(a, b)
    • Take two (non complex) numbers as arguments and return a pair of numbers consisting of their quotient and remainder when using long division.
    • With mixed operand types, the rules for binary arithmetic operators apply.
    • For plain and long integers, the result is the same as ``(a // b, a % b)``.
    • For floating point numbers the result is ``(q, a % b)``, where *q* is usually ``math.floor(a / b)`` but may be 1 less than that.
    • In any case ``q* b + a % b`` is very close to *a*, if ``a % b`` is non-zero it has the same sign as *b*, and ``0 <= abs(a % b) < abs(b)``.
  18. enumerate(sequence[, start=0])
    • Return an enumerate object. *sequence* must be a sequence, an *iterator*, or some other object which supports iteration.
    • The ``next()`` method of the iterator returned by ``enumerate()`` returns a tuple containing a count (from *start* which defaults to 0) and the values obtained from iterating over *sequence*:
    • >>> seasons = ['Spring', 'Summer', 'Fall', 'Winter']
    • >>> list(enumerate(seasons))
    • [(0, 'Spring'), (1, 'Summer'), (2, 'Fall'), (3, 'Winter')]
    • >>> list(enumerate(seasons, start=1))
    • [(1, 'Spring'), (2, 'Summer'), (3, 'Fall'), (4, 'Winter')]
    • Equivalent to:
    • def enumerate(sequence, start=0):
    • n = start
    • for elem in sequence:
    • yield n, elem
    • n += 1
  19. eval(expression[, globals[, locals]])
    • The arguments are a string and optional globals and locals. If provided, *globals* must be a dictionary. If provided, *locals* can be any mapping object.
    • The *expression* argument is parsed and evaluated as a Python expression (technically speaking, a condition list) using the *globals* and *locals* dictionaries as global and local namespace.
    • If the *globals* dictionary is present and lacks '__builtins__', the current globals are copied into *globals* before *expression* is parsed. This means that *expression* normally has full access to the standard ``__builtin__`` module and restricted environments are propagated.
    • If the *locals* dictionary is omitted it defaults to the *globals* dictionary.
    • If both dictionaries are omitted, the expression is executed in the environment where ``eval()`` is called.
    • The return value is the result of the evaluated expression. Syntax errors are reported as exceptions.
    • Example:
    • >>> x = 1
    • >>> print eval('x+1')
    • 2
  20. execfile(filename[, globals[, locals]])
    • This function is similar to the ``exec`` statement, but parses a file instead of a string.
    • It is different from the ``import`` statement in that it does not use the module administration --- it reads the file unconditionally and does not create a new module.
    • Argument 1: The arguments are a file name and two optional dictionaries. The file is parsed and evaluated as a sequence of Python statements (similarly to a module) using the *globals* and *locals* dictionaries as global and local namespace.
    • If provided, *locals* can be any mapping object.
    • If the *locals* dictionary is omitted it defaults to the *globals* dictionary.
    • If both dictionaries are omitted, the expression is executed in the environment where ``execfile()`` is called. The return value is ``None``.
  21. file(filename[, mode[, bufsize]])
    • Constructor function for the ``file`` type, described further in section *File Objects*.
    • The constructor's arguments are the same as those of the ``open()`` built-in function described below.
    • When opening a file, it's preferable to use ``open()`` instead of invoking this constructor directly.
    • ``file`` is more suited to type testing (for example, writing ``isinstance(f, file)``).
  22. filter(function, iterable)
    • Construct a list from those elements of *iterable* for which *function* returns true.
    • *iterable* may be either a sequence, a container which supports iteration, or an iterator.
    • If *iterable* is a string or a tuple, the result also has that type; otherwise it is always a list.
    • If *function* is ``None``, the identity function is assumed, that is, all elements of *iterable* that are false are removed.
    • Note that ``filter(function, iterable)`` is equivalent to ``[item for item in iterable if function(item)]`` if function is not ``None`` and ``[item for item in iterable if item]`` if function is ``None``.
    • See ``itertools.ifilter()`` and ``itertools.ifilterfalse()`` for iterator versions of this function, including a variation that filters for elements where the *function* returns false.
  23. float([x])
    • Convert a string or a number to floating point.
    • If the argument is a string, it must contain a possibly signed decimal or floating point number, possibly embedded in whitespace.
    • The argument may also be [+|-]nan or [+|-]inf. Otherwise, the argument may be a plain or long integer or a floating point number, and a floating point number with the same value (within Python's floating point precision) is returned.
    • If no argument is given, returns ``0.0``.
    • Note: When passing in a string, values for NaN and Infinity may be returned, depending on the underlying C library. Float accepts the strings nan, inf and -inf for NaN and positive or negative infinity. The case and a leading + are ignored as well as a leading - is ignored for NaN. Float always represents NaN and infinity as nan, inf or -inf.
  24. format(value[, format_spec])
    • Convert a *value* to a "formatted" representation, as controlled by *format_spec*.
    • The interpretation of *format_spec* will depend on the type of the *value* argument, however there is a standard formatting syntax that is used by most built-in types. *Format Specification Mini-Language*.
    • Note: ``format(value, format_spec)`` merely calls ``value.__format__(format_spec)``.
  25. frozenset([iterable])
    • Return a frozenset object, optionally with elements taken from *iterable*. The frozenset type is described in *Set Types --- set, frozenset*.
    • For other containers see the built in ``dict``, ``list``, and ``tuple`` classes, and the ``collections`` module.
  26. getattr(object, name[, default])
    • Return the value of the named attribute of *object*.
    • *name* must be a string. If the string is the name of one of the object's attributes, the result is the value of that attribute.
    • For example, ``getattr(x, 'foobar')`` is equivalent to ``x.foobar``.
    • If the named attribute does not exist, *default* is returned if provided, otherwise ``AttributeError`` is raised.
  27. globals()
    • Return a dictionary representing the current global symbol table.
    • This is always the dictionary of the current module (inside a function or method, this is the module where it is defined, not the module from which it is called).
  28. hasattr(object, name)
    • The arguments are an object and a string. The result is ``True`` if the string is the name of one of the object's attributes, ``False`` if not.
    • (This is implemented by calling ``getattr(object,name)`` and seeing whether it raises an exception or not.)
  29. hash(object)
    • Return the hash value of the object (if it has one). Hash values are integers. They are used to quickly compare dictionary keys during a dictionary lookup.
    • Numeric values that compare equal have the same hash value (even if they are of different types, as is the case for 1 and 1.0).
  30. help([object])
    • Invoke the built-in help system. (This function is intended for interactive use.)
    • If no argument is given, the interactive help system starts on the interpreter console.
    • If the argument is a string, then the string is looked up as the name of a module, function, class, method, keyword, or documentation topic, and a help page is printed on the console. If the argument is any other kind of object, a help page on the object is generated.
  31. hex(x)
    • Convert an integer number (of any size) to a hexadecimal string. The result is a valid Python expression.
    • Note: To obtain a hexadecimal string representation for a float, use the ``float.hex()`` method.
  32. id(object)
    • Return the "identity" of an object. This is an integer (or long integer) which is guaranteed to be unique and constant for this object during its lifetime.
    • Two objects with non-overlapping lifetimes may have the same ``id()`` value.
    • **CPython implementation detail:** This is the address of the object in memory.
  33. input([prompt])
    • Equivalent to ``eval(raw_input(prompt))``.
    • Note: This function does not catch user errors. It expects a valid Python expression as input. If the input is not syntactically valid, a ``SyntaxError`` will be raised. Other exceptions may be raised if there is an error during evaluation.
    • If the ``readline`` module was loaded, then ``input()`` will use it to provide elaborate line editing and history features.
    • Consider using the ``raw_input()`` function for general input from users.
  34. int([x[, base]])
    • Convert a string or number to a plain integer.
    • If the argument is a string, it must contain a possibly signed decimal number representable as a Python integer, possibly embedded in whitespace.
    • The *base* parameter gives the base for the conversion (which is 10 by default) and may be any integer in the range [2, 36], or zero.
    • If *base* is zero, the proper radix is determined based on the contents of string; the interpretation is the same as for integer literals. (See *Numeric literals*.)
    • If *base* is specified and *x* is not a string, ``TypeError`` is raised. Otherwise, the argument may be a plain or long integer or a floating point number.
    • Conversion of floating point numbers to integers truncates (towards zero). If the argument is outside the integer range a long object will be returned instead. If no arguments are given, returns ``0``.
  35. isinstance(object, classinfo)
    • Return true if the *object* argument is an instance of the *classinfo* argument, or of a (direct, indirect or *virtual*) subclass thereof.
    • Also return true if *classinfo* is a type object (new-style class) and *object* is an object of that type or of a (direct, indirect or *virtual*) subclass thereof.
    • If *object* is not a class instance or an object of the given type, the function always returns false.
    • If *classinfo* is neither a class object nor a type object, it may be a tuple of class or type objects, or may recursively contain other such tuples (other sequence types are not accepted).
    • If *classinfo* is not a class, type, or tuple of classes, types, and such tuples, a ``TypeError`` exception is raised.
  36. issubclass(class, classinfo)
    • Return true if *class* is a subclass (direct, indirect or *virtual*) of *classinfo*.
    • A class is considered a subclass of itself.
    • *classinfo* may be a tuple of class objects, in which case every entry in *classinfo* will be checked. In any other case, a ``TypeError`` exception is raised.
  37. iter(o[, sentinel])
    • Return an *iterator* object. The first argument is interpreted very differently depending on the presence of the second argument.
    • Without a second argument, *o* must be a collection object which supports the iteration protocol (the ``__iter__()`` method), or it must support the sequence protocol (the ``__getitem__()`` method with integer arguments starting at ``0``).
    • If it does not support either of those protocols, ``TypeError`` is raised.
    • If the second argument, *sentinel*, is given, then *o* must be a callable object.
    • The iterator created in this case will call *o* with no arguments for each call to its ``next()`` method; if the value returned is equal to *sentinel*, ``StopIteration`` will be raised, otherwise the value will be returned.
    • One useful application of the second form of ``iter()`` is to read lines of a file until a certain line is reached. The following example reads a file until the ``readline()`` method returns an empty string:
    • Example:
    • with open('mydata.txt') as fp:
    • for line in iter(fp.readline, ''):
    • process_line(line)
  38. len(s)
    Return the length (the number of items) of an object. The argument may be a sequence (string, tuple or list) or a mapping (dictionary).
  39. list([iterable])
    • Return a list whose items are the same and in the same order as *iterable*'s items.
    • *iterable* may be either a sequence, a container that supports iteration, or an iterator object.
    • If *iterable* is already a list, a copy is made and returned, similar to ``iterable[:]``.
    • For instance, ``list('abc')`` returns ``['a', 'b', 'c']`` and ``list( (1, 2, 3) )`` returns ``[1, 2, 3]``. If no argument is given, returns a new empty list, ``[]``.
  40. locals()
    • Update and return a dictionary representing the current local symbol table.
    • Free variables are returned by ``locals()`` when it is called in function blocks, but not in class blocks.
    • Note: The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter.
  41. long([x[, base]])
    • Convert a string or number to a long integer.
    • If the argument is a string, it must contain a possibly signed number of arbitrary size, possibly embedded in whitespace.
    • The *base* argument is interpreted in the same way as for ``int()``, and may only be given when *x* is a string.
    • Otherwise, the argument may be a plain or long integer or a floating point number, and a long integer with the same value is returned.
    • Conversion of floating point numbers to integers truncates (towards zero). If no arguments are given, returns ``0L``.
  42. map(function, iterable, ...)
    • Apply *function* to every item of *iterable* and return a list of the results.
    • If additional *iterable* arguments are passed, *function* must take that many arguments and is applied to the items from all iterables in parallel.
    • If one iterable is shorter than another it is assumed to be extended with ``None`` items.
    • If *function* is ``None``, the identity function is assumed; if there are multiple arguments, ``map()`` returns a list consisting of tuples containing the corresponding items from all iterables (a kind of transpose operation).
    • The *iterable* arguments may be a sequence or any iterable object; the result is always a list.
  43. max(iterable[, args...][, key])
    • With a single argument *iterable*, return the largest item of a non-empty iterable (such as a string, tuple or list).
    • With more than one argument, return the largest of the arguments.
    • The optional *key* argument specifies a one-argument ordering function like that used for ``list.sort()``. The *key* argument, if supplied, must be in keyword form (for example, ``max(a,b,c,key=func)``).
  44. memoryview(obj)
    • Return a "memory view" object created from the given argument.
    • See *memoryview type* for more information.
  45. min(iterable[, args...][, key])
    • With a single argument *iterable*, return the smallest item of a non-empty iterable (such as a string, tuple or list). With more than one argument, return the smallest of the arguments.
    • The optional *key* argument specifies a one-argument ordering function like that used for ``list.sort()``. The *key* argument, if supplied, must be in keyword form (for example, ``min(a,b,c,key=func)``).
  46. next(iterator[, default])
    • Retrieve the next item from the *iterator* by calling its ``next()`` method.
    • If *default* is given, it is returned if the iterator is exhausted, otherwise ``StopIteration`` is raised.
  47. object()
    • Return a new featureless object.
    • ``object`` is a base for all new style classes.
    • It has the methods that are common to all instances of new style classes.
  48. oct(x)
    • Convert an integer number (of any size) to an octal string.
    • The result is a valid Python expression.
  49. open(name[, mode[, buffering]])
    • Open a file, returning an object of the ``file`` type described in section *File Objects*.
    • If the file cannot be opened, ``IOError`` is raised. When opening a file, it's preferable to use ``open()`` instead of invoking the ``file`` constructor directly.
    • The first two arguments are the same as for ``stdio``'s ``fopen()``: *name* is the file name to be opened, and *mode* is a string indicating how the file is to be opened.
    • The most commonly-used values of *mode* are ``'r'`` for reading, ``'w'`` for writing (truncating the file if it already exists), and ``'a'`` for appending (which on *some* Unix systems means that *all* writes append to the end of the file regardless of the current seek position). If *mode* is omitted, it defaults to ``'r'``. The default is to use text mode, which may convert ``'\n'`` characters to a platform-specific representation on writing and back on reading. Thus, when opening a binary file, you should append ``'b'`` to the *mode* value to open the file in binary mode, which will improve portability. (Appending ``'b'`` is useful even on systems that don't treat binary and text files differently, where it serves as documentation.) See below for more possible values of *mode*.
    • The optional *buffering* argument specifies the file's desired buffer size: 0 means unbuffered, 1 means line buffered, any other positive value means use a buffer of (approximately) that size. A negative *buffering* means to use the system default, which is usually line buffered for tty devices and fully buffered for other files. If omitted, the system default is used. [2]
    • Modes ``'r+'``, ``'w+'`` and ``'a+'`` open the file for updating (note that ``'w+'`` truncates the file). Append ``'b'`` to the mode to open the file in binary mode, on systems that differentiate between binary and text files; on systems that don't have this distinction, adding the ``'b'`` has no effect.
    • In addition to the standard ``fopen()`` values *mode* may be ``'U'`` or ``'rU'``. Python is usually built with universal newline support; supplying ``'U'`` opens the file as a text file, but lines may be terminated by any of the following, the Unix end- of-line convention ``'\n'``, the Macintosh convention ``'\r'``, or the Windows convention ``'\r\n'``. All of these external representations are seen as ``'\n'`` by the Python program. If Python is built without universal newline support a *mode* with ``'U'`` is the same as normal text mode. Note that file objects so opened also have an attribute called ``newlines`` which has a value of ``None`` (if no newlines have yet been seen), ``'\n'``, ``'\r'``, ``'\r\n'``, or a tuple containing all the newline types seen.
    • Python enforces that the mode, after stripping ``'U'``, begins with ``'r'``, ``'w'`` or ``'a'``.
    • Python provides many file handling modules including ``fileinput``, ``os``, ``os.path``, ``tempfile``, and ``shutil``.
  50. ord(c)
    • Given a string of length one, return an integer representing the Unicode code point of the character when the argument is a unicode object, or the value of the byte when the argument is an 8-bit string.
    • For example, ``ord('a')`` returns the integer ``97``, ``ord(u'\u2020')`` returns ``8224``.
    • This is the inverse of ``chr()`` for 8-bit strings and of ``unichr()`` for unicode objects.
    • If a unicode argument is given and Python was built with UCS2 Unicode, then the character's code point must be in the range [0..65535] inclusive; otherwise the string length is two, and a ``TypeError`` will be raised.
  51. pow(x, y[, z])
    • Return *x* to the power *y*;
    • if *z* is present, return *x* to the power *y*, modulo *z* (computed more efficiently than ``pow(x, y) % z``).
    • The two-argument form ``pow(x, y)`` is equivalent to using the power operator: ``x**y``.
    • The arguments must have numeric types. With mixed operand types, the coercion rules for binary arithmetic operators apply. For int and long int operands, the result has the same type as the operands (after coercion) unless the second argument is negative; in that case, all arguments are converted to float and a float result is delivered.
    • For example, ``10**2`` returns ``100``, but ``10**-2`` returns ``0.01``.
    • If the second argument is negative, the third argument must be omitted.
    • If *z* is present, *x* and *y* must be of integer types, and *y* must be non-negative.
  52. print([object, ...][, sep=' '][, end='\n'][, file=sys.stdout])
    • Print *object*(s) to the stream *file*, separated by *sep* and followed by *end*. *sep*, *end* and *file*, if present, must be given as keyword arguments.
    • All non-keyword arguments are converted to strings like ``str()`` does and written to the stream, separated by *sep* and followed by *end*.
    • Both *sep* and *end* must be strings; they can also be ``None``, which means to use the default values. If no *object* is given, ``print()`` will just write *end*.
    • The *file* argument must be an object with a ``write(string)`` method; if it is not present or ``None``, ``sys.stdout`` will be used.
    • Note: This function is not normally available as a built-in since the name ``print`` is recognized as the ``print`` statement. To disable the statement and use the ``print()`` function, use this future statement at the top of your module: from __future__ import print_function
  53. property([fget[, fset[, fdel[, doc]]]])
    • Return a property attribute for *new-style class*es (classes that derive from ``object``).
    • *fget* is a function for getting an attribute value, likewise *fset* is a function for setting, and *fdel* a function for del'ing, an attribute. Typical use is to define a managed attribute ``x``:
    • class C(object):
    • def __init__(self):
    • self._x = None
    • def getx(self):
    • return self._x
    • def setx(self, value):
    • self._x = value
    • def delx(self):
    • del self._x
    • x = property(getx, setx, delx, "I'm the 'x' property.")
    • If then *c* is an instance of *C*, ``c.x`` will invoke the getter, ``c.x = value`` will invoke the setter and ``del c.x`` the deleter.
    • If given, *doc* will be the docstring of the property attribute.
    • Otherwise, the property will copy *fget*'s docstring (if it exists). This makes it possible to create read-only properties easily using ``property()`` as a *decorator*:
    • class Parrot(object):
    • def __init__(self):
    • self._voltage = 100000
    • @property
    • def voltage(self):
    • """Get the current voltage."""
    • return self._voltage
    • turns the ``voltage()`` method into a "getter" for a read-only
    • attribute with the same name.
    • A property object has ``getter``, ``setter``, and ``deleter`` methods usable as decorators that create a copy of the property with the corresponding accessor function set to the decorated function. This is best explained with an example:
    • class C(object):
    • def __init__(self):
    • self._x = None
    • @property
    • def x(self):
    • """I'm the 'x' property."""
    • return self._x
    • @x.setter
    • def x(self, value):
    • self._x = value
    • @x.deleter
    • def x(self):
    • del self._x
    • This code is exactly equivalent to the first example. Be sure to give the additional functions the same name as the original property (``x`` in this case.)
    • The returned property also has the attributes ``fget``, ``fset``, and ``fdel`` corresponding to the constructor arguments.
  54. range([start], stop[, step])
    • This is a versatile function to create lists containing arithmetic progressions.
    • It is most often used in ``for`` loops. The arguments must be plain integers.
    • If the *step* argument is omitted, it defaults to ``1``.
    • If the *start* argument is omitted, it defaults to ``0``.
    • The full form returns a list of plain integers ``[start, start + step, start + 2 * step, ...]``.
    • If *step* is positive, the last element is the largest ``start + i * step`` less than *stop*; if *step* is negative, the last element is the smallest ``start + i * step`` greater than *stop*. *step* must not be zero (or else ``ValueError`` is raised). Example:
    • >>> range(10)
    • [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
    • >>> range(1, 11)
    • [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    • >>> range(0, 30, 5)
    • [0, 5, 10, 15, 20, 25]
    • >>> range(0, 10, 3)
    • [0, 3, 6, 9]
    • >>> range(0, -10, -1)
    • [0, -1, -2, -3, -4, -5, -6, -7, -8, -9]
    • >>> range(0)
    • []
    • >>> range(1, 0)
    • []
  55. raw_input([prompt])
    • If the *prompt* argument is present, it is written to standard output without a trailing newline.
    • The function then reads a line from input, converts it to a string (stripping a trailing newline), and returns that. When EOF is read, ``EOFError`` is raised.
    • Example:
    • >>> s = raw_input('--> ')
    • --> Monty Python's Flying Circus
    • >>> s
    • "Monty Python's Flying Circus"
    • If the ``readline`` module was loaded, then ``raw_input()`` will use it to provide elaborate line editing and history features.
  56. reduce(function, iterable[, initializer])
    • Apply *function* of two arguments cumulatively to the items of *iterable*, from left to right, so as to reduce the iterable to a single value.
    • For example, ``reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])`` calculates ``((((1+2)+3)+4)+5)``.
    • The left argument, *x*, is the accumulated value and the right argument, *y*, is the update value from the *iterable*.
    • If the optional *initializer* is present, it is placed before the items of the iterable in the calculation, and serves as a default when the iterable is empty.
    • If *initializer* is not given and *iterable* contains only one item, the first item is returned.
  57. reload(module)
    • Reload a previously imported *module*. The argument must be a module object, so it must have been successfully imported before.
    • This is useful if you have edited the module source file using an external editor and want to try out the new version without leaving the Python interpreter. The return value is the module object (the same as the *module* argument).
    • When ``reload(module)`` is executed:
    • * Python modules' code is recompiled and the module-level code reexecuted, defining a new set of objects which are bound to names in the module's dictionary. The ``init`` function of extension modules is not called a second time.
    • * As with all other objects in Python the old objects are only reclaimed after their reference counts drop to zero.
    • * The names in the module namespace are updated to point to any new or changed objects.
    • * Other references to the old objects (such as names external to the module) are not rebound to refer to the new objects and must be updated in each namespace where they occur if that is desired.
    • There are a number of other caveats:
    • * If a module is syntactically correct but its initialization fails, the first ``import`` statement for it does not bind its name locally, but does store a (partially initialized) module object in ``sys.modules``. To reload the module you must first ``import`` it again (this will bind the name to the partially initialized module object) before you can ``reload()`` it.
    • * When a module is reloaded, its dictionary (containing the module's global variables) is retained. Redefinitions of names will override the old definitions, so this is generally not a problem. If the new version of a module does not define a name that was defined by the old version, the old definition remains. This feature can be used to the module's advantage if it maintains a global table or cache of objects --- with a ``try`` statement it can test for the table's presence and skip its initialization if desired:
    • try:
    • cache
    • except NameError:
    • cache = {}
    • * It is legal though generally not very useful to reload built-in or dynamically loaded modules, except for ``sys``, ``__main__`` and ``__builtin__``. In many cases, however, extension modules are not designed to be initialized more than once, and may fail in arbitrary ways when reloaded.
    • * If a module imports objects from another module using ``from`` ... ``import`` ..., calling ``reload()`` for the other module does not redefine the objects imported from it --- one way around this is to re-execute the ``from`` statement, another is to use ``import`` and qualified names (*module*.*name*) instead.
    • * If a module instantiates instances of a class, reloading the module that defines the class does not affect the method definitions of the instances --- they continue to use the old class definition. The same is true for derived classes.
  58. repr(object)
    • Return a string containing a printable representation of an object.
    • This is the same value yielded by conversions (reverse quotes). It is sometimes useful to be able to access this operation as an ordinary function.
    • For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to ``eval()``, otherwise the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object.
    • A class can control what this function returns for its instances by defining a ``__repr__()`` method.
  59. reversed(seq)
    Return a reverse *iterator*. *seq* must be an object which has a ``__reversed__()`` method or supports the sequence protocol (the ``__len__()`` method and the ``__getitem__()`` method with integer arguments starting at ``0``).
  60. round(x[, n])
    • Return the floating point value *x* rounded to *n* digits after the decimal point.
    • If *n* is omitted, it defaults to zero.
    • The result is a floating point number.
    • Values are rounded to the closest multiple of 10 to the power minus *n*; if two multiples are equally close, rounding is done away from 0 (so. for example, ``round(0.5)`` is ``1.0`` and ``round(-0.5)`` is ``-1.0``).
    • Note: The behavior of ``round()`` for floats can be surprising: for example, ``round(2.675, 2)`` gives ``2.67`` instead of the expected ``2.68``. This is not a bug: it's a result of the fact that most decimal fractions can't be represented exactly as a float. See *Floating Point Arithmetic: Issues and Limitations* for more information.
  61. set([iterable])
    • Return a new set, optionally with elements taken from *iterable*.
    • The set type is described in *Set Types --- set, frozenset*.
  62. setattr(object, name, value)
    • This is the counterpart of ``getattr()``. The arguments are an object, a string and an arbitrary value. The string may name an existing attribute or a new attribute.
    • The function assigns the value to the attribute, provided the object allows it.
    • For example, ``setattr(x, 'foobar', 123)`` is equivalent to ``x.foobar = 123``.
  63. slice([start], stop[, step])
    • Return a *slice* object representing the set of indices specified by ``range(start, stop, step)``.
    • The *start* and *step* arguments default to ``None``.
    • Slice objects have read-only data attributes ``start``, ``stop`` and ``step`` which merely return the argument values (or their default).
    • They have no other explicit functionality; however they are used by Numerical Python and other third party extensions.
    • Slice objects are also generated when extended indexing syntax is used.
    • For example: ``a[start:stop:step]`` or ``a[start:stop, i]``. See ``itertools.islice()`` for an alternate version that returns an iterator.
  64. sorted(iterable[, cmp[, key[, reverse]]])
    • Return a new sorted list from the items in *iterable*.
    • The optional arguments *cmp*, *key*, and *reverse* have the same meaning as those for the ``list.sort()`` method (described in section *Mutable Sequence Types*).
    • *cmp* specifies a custom comparison function of two arguments (iterable elements) which should return a negative, zero or positive number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument. ``cmp=lambda x,y. cmp(x.lower(), y.lower())``. The default value is ``None``.
    • *key* specifies a function of one argument that is used to extract a comparison key from each list element. ``key=str.lower``. The default value is ``None`` (compare the elements directly).
    • *reverse* is a boolean value. If set to ``True``, then the list elements are sorted as if each comparison were reversed.
    • In general, the *key* and *reverse* conversion processes are much faster than specifying an equivalent *cmp* function. This is because *cmp* is called multiple times for each list element while *key* and *reverse* touch each element only once. Use ``functools.cmp_to_key()`` to convert an old-style *cmp* function to a *key* function.
  65. staticmethod(function)
    • Return a static method for *function*.
    • A static method does not receive an implicit first argument. To declare a static method, use this idiom:
    • class C:
    • @staticmethod
    • def f(arg1, arg2, ...): ...
    • The ``@staticmethod`` form is a function *decorator* -- see the description of function definitions in *Function definitions* for details.
    • It can be called either on the class (such as ``C.f()``) or on an instance (such as ``C().f()``). The instance is ignored except for its class.
    • Static methods in Python are similar to those found in Java or C++.
    • Also see ``classmethod()`` for a variant that is useful for creating alternate class constructors.
  66. str([object])
    • Return a string containing a nicely printable representation of an object.
    • For strings, this returns the string itself.
    • The difference with ``repr(object)`` is that ``str(object)`` does not always attempt to return a string that is acceptable to ``eval()``; its goal is to return a printable string. If no argument is given, returns the empty string, ``''``.
  67. sum(iterable[, start])
    • Sums *start* and the items of an *iterable* from left to right and returns the total.
    • *start* defaults to ``0``. The *iterable*'s items are normally numbers, and the start value is not allowed to be a string.
    • For some use cases, there are good alternatives to ``sum()``. The preferred, fast way to concatenate a sequence of strings is by calling ``''.join(sequence)``.
    • To add floating point values with extended precision, see ``math.fsum()``. To concatenate a series of iterables, consider using ``itertools.chain()``.
  68. super(type[, object-or-type])
    • Return a proxy object that delegates method calls to a parent or sibling class of *type*.
    • This is useful for accessing inherited methods that have been overridden in a class. The search order is same as that used by ``getattr()`` except that the *type* itself is skipped.
    • The ``__mro__`` attribute of the *type* lists the method resolution search order used by both ``getattr()`` and ``super()``. The attribute is dynamic and can change whenever the inheritance hierarchy is updated.
    • If the second argument is omitted, the super object returned is unbound. If the second argument is an object, ``isinstance(obj, type)`` must be true. If the second argument is a type, ``issubclass(type2, type)`` must be true (this is useful for classmethods).
    • Note: ``super()`` only works for *new-style class*es.
    • There are two typical use cases for *super*. In a class hierarchy with single inheritance, *super* can be used to refer to parent classes without naming them explicitly, thus making the code more maintainable. This use closely parallels the use of *super* in other programming languages.
    • The second use case is to support cooperative multiple inheritance in a dynamic execution environment. This use case is unique to Python and is not found in statically compiled languages or languages that only support single inheritance. This makes it possible to implement "diamond diagrams" where multiple base classes implement the same method. Good design dictates that this method have the same calling signature in every case (because the order of calls is determined at runtime, because that order adapts to changes in the class hierarchy, and because that order can include sibling classes that are unknown prior to runtime).
    • For both use cases, a typical superclass call looks like this:
    • class C(B):
    • def method(self, arg):
    • super(C, self).method(arg)
    • Note that ``super()`` is implemented as part of the binding process for explicit dotted attribute lookups such as ``super().__getitem__(name)``. It does so by implementing its own ``__getattribute__()`` method for searching classes in a predictable order that supports cooperative multiple inheritance.
    • Accordingly, ``super()`` is undefined for implicit lookups using statements or operators such as ``super()[name]``.
    • Also note that ``super()`` is not limited to use inside methods. The two argument form specifies the arguments exactly and makes the appropriate references.
  69. tuple([iterable])
    • Return a tuple whose items are the same and in the same order as *iterable*'s items.
    • *iterable* may be a sequence, a container that supports iteration, or an iterator object.
    • If *iterable* is already a tuple, it is returned unchanged.
    • For instance, ``tuple('abc')`` returns ``('a', 'b', 'c')`` and ``tuple([1, 2, 3])`` returns ``(1, 2, 3)``. If no argument is given, returns a new empty tuple, ``()``.
    • ``tuple`` is an immutable sequence type.
  70. type(object)
    • Return the type of an *object*. The return value is a type object.
    • The ``isinstance()`` built-in function is recommended for testing the type of an object.
    • With three arguments, ``type()`` functions as a constructor as detailed below.
  71. type(name, bases, dict)
    • Return a new type object. This is essentially a dynamic form of the ``class`` statement.
    • The *name* string is the class name and becomes the ``__name__`` attribute;
    • the *bases* tuple itemizes the base classes and becomes the ``__bases__`` attribute;
    • and the *dict* dictionary is the namespace containing definitions for class body and becomes the ``__dict__`` attribute.
    • For example, the following two statements create identical ``type`` objects:
    • >>> class X(object):
    • ... a = 1
    • ...
    • >>> X = type('X', (object,), dict(a=1))
  72. unichr(i)
    • Return the Unicode string of one character whose Unicode code is the integer *i*. For example, ``unichr(97)`` returns the string ``u'a'``.
    • This is the inverse of ``ord()`` for Unicode strings.
    • The valid range for the argument depends how Python was configured -- it may be either UCS2 [0..0xFFFF] or UCS4 [0..0x10FFFF].
    • ``ValueError`` is raised otherwise. For ASCII and 8-bit strings see ``chr()``.
  73. unicode([object[, encoding[, errors]]])
    • Return the Unicode string version of *object* using one of the following modes:
    • 1. If *encoding* and/or *errors* are given, ``unicode()`` will decode the object which can either be an 8-bit string or a character buffer using the codec for *encoding*. The *encoding* parameter is a string giving the name of an encoding; if the encoding is not known, ``LookupError`` is raised. Error handling is done according to *errors*; this specifies the treatment of characters which are invalid in the input encoding. If *errors* is ``'strict'`` (the default), a ``ValueError`` is raised on errors, while a value of ``'ignore'`` causes errors to be silently ignored, and a value of ``'replace'`` causes the official Unicode replacement character, ``U+FFFD``, to be used to replace input characters which cannot be decoded. See also the ``codecs`` module.
    • 2. If no optional parameters are given, ``unicode()`` will mimic the behaviour of ``str()`` except that it returns Unicode strings instead of 8-bit strings. More precisely, if *object* is a Unicode string or subclass it will return that Unicode string without any additional decoding applied.
    • 3. For objects which provide a ``__unicode__()`` method, it will call this method without arguments to create a Unicode string. For all other objects, the 8-bit string version or representation is requested and then converted to a Unicode string using the codec for the default encoding in ``'strict'`` mode.
    • 4. For more information on Unicode strings see *Sequence Types --- str, unicode, list, tuple, bytearray, buffer, xrange* which describes sequence functionality (Unicode strings are sequences), and also the string-specific methods described in the *String Methods* section. To output formatted strings use template strings or the ``%`` operator described in the *String Formatting Operations* section. In addition see the *String Services* section. See also ``str()``.
  74. vars([object])
    • Without an argument, act like ``locals()``.
    • With a module, class or class instance object as argument (or anything else that has a ``__dict__`` attribute), return that attribute.
    • Note: The returned dictionary should not be modified: the effects on the corresponding symbol table are undefined. [3]
  75. xrange([start], stop[, step])
    • This function is very similar to ``range()``, but returns an "xrange object" instead of a list.
    • This is an opaque sequence type which yields the same values as the corresponding list, without actually storing them all simultaneously.
    • The advantage of ``xrange()`` over ``range()`` is minimal (since ``xrange()`` still has to create the values when asked for them) except when a very large range is used on a memory-starved machine or when all of the range's elements are never used (such as when the loop is usually terminated with ``break``).
    • **CPython implementation detail:** ``xrange()`` is intended to be simple and fast. Implementations may impose restrictions to achieve this. The C implementation of Python restricts all arguments to native C longs ("short" Python integers), and also requires that the number of elements fit in a native C long. If a larger range is needed, an alternate version can be crafted using the ``itertools`` module: ``islice(count(start, step), (stop- start+step-1+2*(step<0))//step)``.
  76. zip([iterable, ...])
    • This function returns a list of tuples, where the *i*-th tuple contains the *i*-th element from each of the argument sequences or iterables.
    • The returned list is truncated in length to the length of the shortest argument sequence.
    • When there are multiple arguments which are all of the same length, ``zip()`` is similar to ``map()`` with an initial argument of ``None``.
    • With a single sequence argument, it returns a list of 1-tuples. With no arguments, it returns an empty list.
    • The left-to-right evaluation order of the iterables is guaranteed. This makes possible an idiom for clustering a data series into n-length groups using ``zip(*[iter(s)]*n)``.
    • ``zip()`` in conjunction with the ``*`` operator can be used to unzip a list:
    • >>> x = [1, 2, 3]
    • >>> y = [4, 5, 6]
    • >>> zipped = zip(x, y)
    • >>> zipped
    • [(1, 4), (2, 5), (3, 6)]
    • >>> x2, y2 = zip(*zipped)
    • >>> x == list(x2) and y == list(y2)
    • True

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