
Built-in Functions
******************

The Python interpreter has a number of functions and types built into
it that are always available.  They are listed here in alphabetical
order.

abs(x)

   Return the absolute value of a number.  The argument may be an
   integer or a floating point number.  If the argument is a complex
   number, its magnitude is returned.

all(iterable)

   Return True if all elements of the *iterable* are true (or if the
   iterable is empty).  Equivalent to:

      def all(iterable):
          for element in iterable:
              if not element:
                  return False
          return True

any(iterable)

   Return True if any element of the *iterable* is true.  If the
   iterable is empty, return False.  Equivalent to:

      def any(iterable):
          for element in iterable:
              if element:
                  return True
          return False

ascii(object)

   As ``repr()``, return a string containing a printable
   representation of an object, but escape the non-ASCII characters in
   the string returned by ``repr()`` using ``\x``, ``\u`` or ``\U``
   escapes.  This generates a string similar to that returned by
   ``repr()`` in Python 2.

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.

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``.

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
   *Bytes and Byte Array Methods*.

   The optional *source* parameter can be used to initialize the array
   in a few different ways:

   * 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()``.

   * If it is an *integer*, the array will have that size and will be
     initialized with null bytes.

   * 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.

   * 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.

   Without an argument, an array of size 0 is created.

bytes([source[, encoding[, errors]]])

   Return a new "bytes" object, which is an immutable sequence of
   integers in the range ``0 <= x < 256``.  ``bytes`` is an immutable
   version of ``bytearray`` -- it has the same non-mutating methods
   and the same indexing and slicing behavior.

   Accordingly, constructor arguments are interpreted as for
   ``bytearray()``.

   Bytes objects can also be created with literals, see *String and
   Bytes literals*.

chr(i)

   Return the string of one character whose Unicode codepoint is the
   integer *i*.  For example, ``chr(97)`` returns the string ``'a'``.
   This is the inverse of ``ord()``.  The valid range for the argument
   depends how Python was configured -- it may be either UCS2
   [0..0xFFFF] or UCS4 [0..0x10FFFF]. ``ValueError`` will be raised if
   *i* is outside that range.

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*.

compile(source, filename, mode, flags=0, dont_inherit=False)

   Compile the *source* into a code or AST object.  Code objects can
   be executed by:func:*exec* or ``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.

   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 (``'<string>'`` is commonly used).

   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).

   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 statements, line endings
     must be represented by a single newline character (``'\n'``), and
     the input must be terminated by at least one newline character.
     If line endings are represented by ``'\r\n'``, use
     ``str.replace()`` to change them into ``'\n'``.

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()`` and ``float()``.  If both arguments are omitted, returns
   ``0j``.

   The complex type is described in *Numeric Types --- int, float,
   complex*.

delattr(object, name)

   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.  The function deletes the named attribute, provided the
   object allows it.  For example, ``delattr(x, 'foobar')`` is
   equivalent to ``del x.foobar``.

dict([arg])

   Create a new data dictionary, optionally with items taken from
   *arg*. The dictionary type is described in *Mapping Types ---
   dict*.

   For other containers see the built in ``list``, ``set``, and
   ``tuple`` classes, and the ``collections`` module.

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:

   * If the object is a module object, the list contains the names of
     the module's attributes.

   * 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.

   * 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.

   The resulting list is sorted alphabetically.  For example:

   >>> import struct
   >>> dir()   # doctest: +SKIP
   ['__builtins__', '__doc__', '__name__', 'struct']
   >>> dir(struct)   # doctest: +NORMALIZE_WHITESPACE
   ['Struct', '__builtins__', '__doc__', '__file__', '__name__',
    '__package__', '_clearcache', 'calcsize', 'error', 'pack', 'pack_into',
    'unpack', 'unpack_from']
   >>> class Foo(object):
   ...     def __dir__(self):
   ...         return ["kan", "ga", "roo"]
   ...
   >>> f = Foo()
   >>> dir(f)
   ['ga', 'kan', 'roo']

   Note: Because ``dir()`` is supplied primarily as a convenience for use
     at an interactive prompt, it tries to supply an interesting set
     of names more than it tries to supply a rigorously or
     consistently defined set of names, and its detailed behavior may
     change across releases.  For example, metaclass attributes are
     not in the result list when the argument is a class.

divmod(a, b)

   Take two (non complex) numbers as arguments and return a pair of
   numbers consisting of their quotient and remainder when using
   integer division.  With mixed operand types, the rules for binary
   arithmetic operators apply.  For 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)``.

enumerate(iterable, start=0)

   Return an enumerate object. *iterable* 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 corresponding value obtained from iterating over
   *iterable*. ``enumerate()`` is useful for obtaining an indexed
   series: ``(0, seq[0])``, ``(1, seq[1])``, ``(2, seq[2])``, .... For
   example:

   >>> for i, season in enumerate(['Spring', 'Summer', 'Fall', 'Winter']):
   ...     print(i, season)
   0 Spring
   1 Summer
   2 Fall
   3 Winter

eval(expression, globals=None, locals=None)

   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 ``builtins`` 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
   >>> eval('x+1')
   2

   This function can also be used to execute arbitrary code objects
   (such as those created by ``compile()``).  In this case pass a code
   object instead of a string.  If the code object has been compiled
   with ``'exec'`` as the *kind* argument, ``eval()``'s return value
   will be ``None``.

   Hints: dynamic execution of statements is supported by the
   ``exec()`` function.  The ``globals()`` and ``locals()`` functions
   returns the current global and local dictionary, respectively,
   which may be useful to pass around for use by ``eval()`` or
   ``exec()``.

exec(object[, globals[, locals]])

   This function supports dynamic execution of Python code. *object*
   must be either a string or a code object.  If it is a string, the
   string is parsed as a suite of Python statements which is then
   executed (unless a syntax error occurs). [1] If it is a code
   object, it is simply executed.  In all cases, the code that's
   executed is expected to be valid as file input (see the section
   "File input" in the Reference Manual). Be aware that the ``return``
   and ``yield`` statements may not be used outside of function
   definitions even within the context of code passed to the
   ``exec()`` function. The return value is ``None``.

   In all cases, if the optional parts are omitted, the code is
   executed in the current scope.  If only *globals* is provided, it
   must be a dictionary, which will be used for both the global and
   the local variables.  If *globals* and *locals* are given, they are
   used for the global and local variables, respectively.  If
   provided, *locals* can be any mapping object.

   If the *globals* dictionary does not contain a value for the key
   ``__builtins__``, a reference to the dictionary of the built-in
   module ``builtins`` is inserted under that key.  That way you can
   control what builtins are available to the executed code by
   inserting your own ``__builtins__`` dictionary into *globals*
   before passing it to ``exec()``.

   Note: The built-in functions ``globals()`` and ``locals()`` return the
     current global and local dictionary, respectively, which may be
     useful to pass around for use as the second and third argument to
     ``exec()``.

   Note: The default *locals* act as described for function ``locals()``
     below: modifications to the default *locals* dictionary should
     not be attempted. Pass an explicit *locals* dictionary if you
     need to see effects of the code on *locals* after function
     ``exec()`` returns.

filter(function, iterable)

   Construct an iterator 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 *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 the
   generator expression ``(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.filterfalse()`` for the complementary function that
   returns elements of *iterable* for which *function* returns false.

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 an 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, ``0.0`` is
   returned.

   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``.

   The float type is described in *Numeric Types --- int, float,
   complex*.

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)``.

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.

getattr(object, name[, default])

   Return the value of the named attributed 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.

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).

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.)

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).

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.

   This function is added to the built-in namespace by the ``site``
   module.

hex(x)

   Convert an integer number to a hexadecimal 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.

   Note: To obtain a hexadecimal string representation for a float, use
     the ``float.hex()`` method.

id(object)

   Return the "identity" of an object.  This is an 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.

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 = input('--> ')
      --> Monty Python's Flying Circus
      >>> s
      "Monty Python's Flying Circus"

   If the ``readline`` module was loaded, then ``input()`` will use it
   to provide elaborate line editing and history features.

int([number | string[, base]])

   Convert a number or string to an integer.  If no arguments are
   given, return ``0``.  If a number is given, return
   ``number.__int__()``.  Conversion of floating point numbers to
   integers truncates towards zero.  A string must be a base-radix
   integer literal optionally preceded by '+' or '-' (with no space in
   between) and optionally surrounded by whitespace.  A base-n literal
   consists of the digits 0 to n-1, with 'a' to 'z' (or 'A' to 'Z')
   having values 10 to 35.  The default *base* is 10. The allowed
   values are 0 and 2-36. Base-2, -8, and -16 literals can be
   optionally prefixed with ``0b``/``0B``, ``0o``/``0O``, or
   ``0x``/``0X``, as with integer literals in code.  Base 0 means to
   interpret exactly as a code literal, so that the actual base is 2,
   8, 10, or 16, and so that ``int('010', 0)`` is not legal, while
   ``int('010')`` is, as well as ``int('010', 8)``.

   The integer type is described in *Numeric Types --- int, float,
   complex*.

isinstance(object, classinfo)

   Return true if the *object* argument is an instance of the
   *classinfo* argument, or of a (direct or indirect) subclass
   thereof.  If *object* is not an object of the given type, the
   function always returns false.  If *classinfo* is not a class (type
   object), it may be a tuple of type objects, or may recursively
   contain other such tuples (other sequence types are not accepted).
   If *classinfo* is not a type or tuple of types and such tuples, a
   ``TypeError`` exception is raised.

issubclass(class, classinfo)

   Return true if *class* is a subclass (direct or indirect) 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.

iter(object[, sentinel])

   Return an *iterator* object.  The first argument is interpreted
   very differently depending on the presence of the second argument.
   Without a second argument, *object* 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 *object* must be a
   callable object.  The iterator created in this case will call
   *object* 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 ``"STOP"`` is reached:

      with open("mydata.txt") as fp:
          for line in iter(fp.readline, "STOP"):
              process_line(line)

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).

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, ``[]``.

   ``list`` is a mutable sequence type, as documented in *Sequence
   Types --- str, bytes, bytearray, list, tuple, range*.

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.

map(function, iterable, ...)

   Return an iterator that applies *function* to every item of
   *iterable*, yielding 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.  With
   multiple iterables, the iterator stops when the shortest iterable
   is exhausted.  For cases where the function inputs are already
   arranged into argument tuples, see ``itertools.starmap()``.

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 keyword-only *key* argument specifies a one-argument
   ordering function like that used for ``list.sort()``.

memoryview(obj)

   Return a "memory view" object created from the given argument.  See
   *memoryview Types* for more information.

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 keyword-only *key* argument specifies a one-argument
   ordering function like that used for ``list.sort()``.

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.

object()

   Return a new featureless object.  ``object`` is a base for all
   classes. It has the methods that are common to all instances of
   Python classes.  This function does not accept any arguments.

   Note: ``object`` does *not* have a ``__dict__``, so you can't assign
     arbitrary attributes to an instance of the ``object`` class.

oct(x)

   Convert an integer number to an octal 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.

open(file, mode='r', buffering=None, encoding=None, errors=None, newline=None, closefd=True)

   Open *file* and return a corresponding stream.  If the file cannot
   be opened, an ``IOError`` is raised.

   *file* is either a string or bytes object giving the name (and the
   path if the file isn't in the current working directory) of the
   file to be opened or an integer file descriptor of the file to be
   wrapped.  (If a file descriptor is given, it is closed when the
   returned I/O object is closed, unless *closefd* is set to
   ``False``.)

   *mode* is an optional string that specifies the mode in which the
   file is opened.  The available modes are:

   +-----------+-----------------------------------------------------------------+
   | Character | Meaning                                                         |
   +-----------+-----------------------------------------------------------------+
   | ``'r'``   | open for reading (default)                                      |
   +-----------+-----------------------------------------------------------------+
   | ``'w'``   | open for writing, truncating the file first if it exists        |
   +-----------+-----------------------------------------------------------------+
   | ``'a'``   | open for writing, appending to the end of the file if it exists |
   +-----------+-----------------------------------------------------------------+

   Several characters can be appended that modify the given mode:

   +-----------+-----------------------------------------------------------------+
   | ``'t'``   | text mode (default)                                             |
   +-----------+-----------------------------------------------------------------+
   | ``'b'``   | binary mode                                                     |
   +-----------+-----------------------------------------------------------------+
   | ``'+'``   | open for updating (reading and writing)                         |
   +-----------+-----------------------------------------------------------------+
   | ``'U'``   | universal newline mode (for backwards compatibility; should not |
   |           | be used in new code)                                            |
   +-----------+-----------------------------------------------------------------+

   The mode ``'w+'`` opens and truncates the file to 0 bytes, while
   ``'r+'`` opens the file without truncation.  On *some* Unix
   systems, append mode means that *all* writes append to the end of
   the file regardless of the current seek position.

   Python distinguishes between files opened in binary and text modes,
   even when the underlying operating system doesn't.  Files opened in
   binary mode (including ``'b'`` in the *mode* argument) return
   contents as ``bytes`` objects without any decoding.  In text mode
   (the default, or when ``'t'`` is included in the *mode* argument),
   the contents of the file are returned as strings, the bytes having
   been first decoded using the specified *encoding*. If *encoding* is
   not specified, a platform-dependent default encoding is used, see
   below.

   *buffering* is an optional integer used to set the buffering
   policy.  By default full buffering is on.  Pass 0 to switch
   buffering off (only allowed in binary mode), 1 to set line
   buffering, and an integer > 1 for full buffering.

   *encoding* is the name of the encoding used to decode or encode the
   file. This should only be used in text mode.  The default encoding
   is platform dependent (whatever ``locale.getpreferredencoding()``
   returns), but any encoding supported by Python can be used.  See
   the ``codecs`` module for the list of supported encodings.

   *errors* is an optional string that specifies how encoding and
   decoding errors are to be handled--this cannot be used in binary
   mode.  Pass ``'strict'`` to raise a ``ValueError`` exception if
   there is an encoding error (the default of ``None`` has the same
   effect), or pass ``'ignore'`` to ignore errors.  (Note that
   ignoring encoding errors can lead to data loss.) ``'replace'``
   causes a replacement marker (such as ``'?'``) to be inserted where
   there is malformed data.  When writing, ``'xmlcharrefreplace'``
   (replace with the appropriate XML character reference) or
   ``'backslashreplace'`` (replace with backslashed escape sequences)
   can be used.  Any other error handling name that has been
   registered with ``codecs.register_error()`` is also valid.

   *newline* controls how universal newlines works (it only applies to
   text mode).  It can be ``None``, ``''``, ``'\n'``, ``'\r'``, and
   ``'\r\n'``.  It works as follows:

   * On input, if *newline* is ``None``, universal newlines mode is
     enabled. Lines in the input can end in ``'\n'``, ``'\r'``, or
     ``'\r\n'``, and these are translated into ``'\n'`` before being
     returned to the caller.  If it is ``''``, universal newline mode
     is enabled, but line endings are returned to the caller
     untranslated.  If it has any of the other legal values, input
     lines are only terminated by the given string, and the line
     ending is returned to the caller untranslated.

   * On output, if *newline* is ``None``, any ``'\n'`` characters
     written are translated to the system default line separator,
     ``os.linesep``.  If *newline* is ``''``, no translation takes
     place.  If *newline* is any of the other legal values, any
     ``'\n'`` characters written are translated to the given string.

   If *closefd* is ``False`` and a file descriptor rather than a
   filename was given, the underlying file descriptor will be kept
   open when the file is closed.  If a filename is given *closefd* has
   no effect and must be ``True`` (the default).

   The type of file object returned by the ``open()`` function depends
   on the mode.  When ``open()`` is used to open a file in a text mode
   (``'w'``, ``'r'``, ``'wt'``, ``'rt'``, etc.), it returns a subclass
   of ``io.TextIOBase`` (specifically ``io.TextIOWrapper``).  When
   used to open a file in a binary mode with buffering, the returned
   class is a subclass of ``io.BufferedIOBase``.  The exact class
   varies: in read binary mode, it returns a ``io.BufferedReader``; in
   write binary and append binary modes, it returns a
   ``io.BufferedWriter``, and in read/write mode, it returns a
   ``io.BufferedRandom``.  When buffering is disabled, the raw stream,
   a subclass of ``io.RawIOBase``, ``io.FileIO``, is returned.

   See also the file handling modules, such as, ``fileinput``, ``io``
   (where ``open()`` is declared), ``os``, ``os.path``, ``tempfile``,
   and ``shutil``.

ord(c)

   Given a string of length one, return an integer representing the
   Unicode code point of the character.  For example, ``ord('a')``
   returns the integer ``97`` and ``ord('\u2020')`` returns ``8224``.
   This is the inverse of ``chr()``.

   If the argument length is not one, a ``TypeError`` will be raised.
   (If 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!)

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`` 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.

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.

property(fget=None, fset=None, fdel=None, doc=None)

   Return a property attribute.

   *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 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.

range([start], stop[, step])

   This is a versatile function to create iterables yielding
   arithmetic progressions.  It is most often used in ``for`` loops.
   The arguments must be 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 an iterable of 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:

   >>> list(range(10))
   [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
   >>> list(range(1, 11))
   [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
   >>> list(range(0, 30, 5))
   [0, 5, 10, 15, 20, 25]
   >>> list(range(0, 10, 3))
   [0, 3, 6, 9]
   >>> list(range(0, -10, -1))
   [0, -1, -2, -3, -4, -5, -6, -7, -8, -9]
   >>> list(range(0))
   []
   >>> list(range(1, 0))
   []

repr(object)

   Return a string containing a printable representation of an object.
   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.

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``).

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.  Delegates
   to ``x.__round__(n)``.

   For the built-in types supporting ``round()``, values are rounded
   to the closest multiple of 10 to the power minus *n*; if two
   multiples are equally close, rounding is done toward the even
   choice (so, for example, both ``round(0.5)`` and ``round(-0.5)``
   are ``0``, and ``round(1.5)`` is ``2``). The return value is an
   integer if called with one argument, otherwise of the same type as
   *x*.

set([iterable])

   Return a new set, optionally with elements taken from *iterable*.
   The set type is described in *Set Types --- set, frozenset*.

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``.

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.

sorted(iterable[, key][, reverse])

   Return a new sorted list from the items in *iterable*.

   Has two optional arguments which must be specified as keyword
   arguments.

   *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``.

   *reverse* is a boolean value.  If set to ``True``, then the list
   elements are sorted as if each comparison were reversed.

   To convert an old-style *cmp* function to a *key* function, see the
   CmpToKey recipe in the ASPN cookbook.

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++.
   For a more advanced concept, see ``classmethod()`` in this section.

   For more information on static methods, consult the documentation
   on the standard type hierarchy in *The standard type hierarchy*.

str([object[, encoding[, errors]]])

   Return a string version of an object, using one of the following
   modes:

   If *encoding* and/or *errors* are given, ``str()`` will decode the
   *object* which can either be a byte 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.

   When only *object* is given, this returns its nicely printable
   representation. For strings, this is 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. With no arguments, this
   returns the empty string.

   Objects can specify what ``str(object)`` returns by defining a
   ``__str__()`` special method.

   For more information on strings see *Sequence Types --- str, bytes,
   bytearray, list, tuple, range* which describes sequence
   functionality (strings are sequences), and also the string-specific
   methods described in the *String Methods* section. To output
   formatted strings, see the *String Formatting* section. In addition
   see the *String Services* section.

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 are not allowed to be strings.  The
   fast, correct way to concatenate a sequence of strings is by
   calling ``''.join(sequence)``.  To add floating point values with
   extended precision, see ``math.fsum()``.

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).

   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().method(arg)    # This does the same thing as:
                                     # 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.  The zero argument form automatically
   searches the stack frame for the class (``__class__``) and the
   first argument.

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, as documented in *Sequence
   Types --- str, bytes, bytearray, list, tuple, range*.

type(object)

   Return the type of an *object*.  The return value is a type object
   and generally the same object as returned by ``object.__class__``.

   The ``isinstance()`` built-in function is recommended for testing
   the type of an object, because it takes subclasses into account.

   With three arguments, ``type()`` functions as a constructor as
   detailed below.

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))

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. [2]

zip(*iterables)

   Make an iterator that aggregates elements from each of the
   iterables.

   Returns an iterator of tuples, where the *i*-th tuple contains the
   *i*-th element from each of the argument sequences or iterables.
   The iterator stops when the shortest input iterable is exhausted.
   With a single iterable argument, it returns an iterator of
   1-tuples.  With no arguments, it returns an empty iterator.
   Equivalent to:

      def zip(*iterables):
          # zip('ABCD', 'xy') --> Ax By
          iterables = map(iter, iterables)
          while iterables:
              yield tuple(map(next, iterables))

   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()`` should only be used with unequal length inputs when you
   don't care about trailing, unmatched values from the longer
   iterables.  If those values are important, use
   ``itertools.zip_longest()`` instead.

   ``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)
      >>> list(zipped)
      [(1, 4), (2, 5), (3, 6)]
      >>> x2, y2 = zip(*zip(x, y))
      >>> x == list(x2) and y == list(y2)
      True

__import__(name, globals={}, locals={}, fromlist=[], level=-1)

   Note: This is an advanced function that is not needed in everyday
     Python programming.

   This function is invoked by the ``import`` statement.  It can be
   replaced (by importing the ``builtins`` module and assigning to
   ``builtins.__import__``) in order to change semantics of the
   ``import`` statement, but nowadays it is usually simpler to use
   import hooks (see **PEP 302**).  Direct use of ``__import__()`` is
   rare, except in cases where you want to import a module whose name
   is only known at runtime.

   The function imports the module *name*, potentially using the given
   *globals* and *locals* to determine how to interpret the name in a
   package context. The *fromlist* gives the names of objects or
   submodules that should be imported from the module given by *name*.
   The standard implementation does not use its *locals* argument at
   all, and uses its *globals* only to determine the package context
   of the ``import`` statement.

   *level* specifies whether to use absolute or relative imports.
   ``0`` (the default) means only perform absolute imports.  Positive
   values for *level* indicate the number of parent directories to
   search relative to the directory of the module calling
   ``__import__()``.

   When the *name* variable is of the form ``package.module``,
   normally, the top-level package (the name up till the first dot) is
   returned, *not* the module named by *name*.  However, when a non-
   empty *fromlist* argument is given, the module named by *name* is
   returned.

   For example, the statement ``import spam`` results in bytecode
   resembling the following code:

      spam = __import__('spam', globals(), locals(), [], 0)

   The statement ``import spam.ham`` results in this call:

      spam = __import__('spam.ham', globals(), locals(), [], 0)

   Note how ``__import__()`` returns the toplevel module here because
   this is the object that is bound to a name by the ``import``
   statement.

   On the other hand, the statement ``from spam.ham import eggs,
   sausage as saus`` results in

      _temp = __import__('spam.ham', globals(), locals(), ['eggs', 'sausage'], 0)
      eggs = _temp.eggs
      saus = _temp.sausage

   Here, the ``spam.ham`` module is returned from ``__import__()``.
   From this object, the names to import are retrieved and assigned to
   their respective names.

   If you simply want to import a module (potentially within a
   package) by name, you can call ``__import__()`` and then look it up
   in ``sys.modules``:

      >>> import sys
      >>> name = 'foo.bar.baz'
      >>> __import__(name)
      <module 'foo' from ...>
      >>> baz = sys.modules[name]
      >>> baz
      <module 'foo.bar.baz' from ...>

-[ Footnotes ]-

[1] Note that the parser only accepts the Unix-style end of line
    convention. If you are reading the code from a file, make sure to
    use newline conversion mode to convert Windows or Mac-style
    newlines.

[2] In the current implementation, local variable bindings cannot
    normally be affected this way, but variables retrieved from other
    scopes (such as modules) can be.  This may change.
