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.

+---------------------------+-------------------------+-------------------------+---------------------------+
| Built-in Functions                                                                                        |
|===========================|=========================|=========================|===========================|
| **A** "abs()" "aiter()"   | **E** "enumerate()"     | **L** "len()" "list()"  | **R** "range()" "repr()"  |
| "all()" "anext()" "any()" | "eval()" "exec()"       | "locals()"  **M**       | "reversed()" "round()"    |
| "ascii()"  **B** "bin()"  | **F** "filter()"        | "map()" "max()"         | **S** "set()" "setattr()" |
| "bool()" "breakpoint()"   | "float()" "format()"    | "memoryview()" "min()"  | "slice()" "sorted()"      |
| "bytearray()" "bytes()"   | "frozenset()"  **G**    | **N** "next()"  **O**   | "staticmethod()" "str()"  |
| **C** "callable()"        | "getattr()" "globals()" | "object()" "oct()"      | "sum()" "super()"  **T**  |
| "chr()" "classmethod()"   | **H** "hasattr()"       | "open()" "ord()"  **P** | "tuple()" "type()"  **V** |
| "compile()" "complex()"   | "hash()" "help()"       | "pow()" "print()"       | "vars()"  **Z** "zip()"   |
| **D** "delattr()"         | "hex()"  **I** "id()"   | "property()"            | **_** "__import__()"      |
| "dict()" "dir()"          | "input()" "int()"       |                         |                           |
| "divmod()"                | "isinstance()"          |                         |                           |
|                           | "issubclass()" "iter()" |                         |                           |
+---------------------------+-------------------------+-------------------------+---------------------------+

abs(x)

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

aiter(async_iterable)

   Return an *asynchronous iterator* for an *asynchronous iterable*.
   Equivalent to calling "x.__aiter__()".

   Note: Unlike "iter()", "aiter()" has no 2-argument variant.

   Added in version 3.10.

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

awaitable anext(async_iterator)
awaitable anext(async_iterator, default)

   When awaited, return the next item from the given *asynchronous
   iterator*, or *default* if given and the iterator is exhausted.

   This is the async variant of the "next()" builtin, and behaves
   similarly.

   This calls the "__anext__()" method of *async_iterator*, returning
   an *awaitable*. Awaiting this returns the next value of the
   iterator. If *default* is given, it is returned if the iterator is
   exhausted, otherwise "StopAsyncIteration" is raised.

   Added in version 3.10.

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 prefixed with “0b”.
   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. Some examples:

   >>> bin(3)
   '0b11'
   >>> bin(-10)
   '-0b1010'

   If the prefix “0b” is desired or not, you can use either of the
   following ways.

   >>> format(14, '#b'), format(14, 'b')
   ('0b1110', '1110')
   >>> f'{14:#b}', f'{14:b}'
   ('0b1110', '1110')

   See also "format()" for more information.

class bool(object=False, /)

   Return a Boolean value, i.e. one of "True" or "False".  The
   argument is converted using the standard truth testing procedure.
   If the argument is false or omitted, this returns "False";
   otherwise, it returns "True".  The "bool" class is a subclass of
   "int" (see Numeric Types — int, float, complex). It cannot be
   subclassed further.  Its only instances are "False" and "True" (see
   Boolean Type - bool).

   Changed in version 3.7: The parameter is now positional-only.

breakpoint(*args, **kws)

   This function drops you into the debugger at the call site.
   Specifically, it calls "sys.breakpointhook()", passing "args" and
   "kws" straight through.  By default, "sys.breakpointhook()" calls
   "pdb.set_trace()" expecting no arguments.  In this case, it is
   purely a convenience function so you don’t have to explicitly
   import "pdb" or type as much code to enter the debugger.  However,
   "sys.breakpointhook()" can be set to some other function and
   "breakpoint()" will automatically call that, allowing you to drop
   into the debugger of choice. If "sys.breakpointhook()" is not
   accessible, this function will raise "RuntimeError".

   By default, the behavior of "breakpoint()" can be changed with the
   "PYTHONBREAKPOINT" environment variable. See "sys.breakpointhook()"
   for usage details.

   Note that this is not guaranteed if "sys.breakpointhook()" has been
   replaced.

   Raises an auditing event "builtins.breakpoint" with argument
   "breakpointhook".

   Added in version 3.7.

class bytearray(source=b'')
class bytearray(source, encoding)
class bytearray(source, encoding, errors)

   Return a new array of bytes.  The "bytearray" class 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 "bytes" type has, see Bytes
   and Bytearray Operations.

   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.

   See also Binary Sequence Types — bytes, bytearray, memoryview and
   Bytearray Objects.

class bytes(source=b'')
class bytes(source, encoding)
class 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.

   See also Binary Sequence Types — bytes, bytearray, memoryview,
   Bytes Objects, and Bytes and Bytearray Operations.

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); instances are callable if their class has a "__call__()"
   method.

   Added in version 3.2: This function was first removed in Python 3.0
   and then brought back in Python 3.2.

chr(i)

   Return the string representing a character whose Unicode code point
   is the integer *i*.  For example, "chr(97)" returns the string
   "'a'", while "chr(8364)" returns the string "'€'". This is the
   inverse of "ord()".

   The valid range for the argument is from 0 through 1,114,111
   (0x10FFFF in base 16).  "ValueError" will be raised if *i* is
   outside that range.

@classmethod

   Transform a method into a class method.

   A class method receives the class as an 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 Function
   definitions for details.

   A class method 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, see The standard type hierarchy.

   Changed in version 3.9: Class methods can now wrap other
   *descriptors* such as "property()".

   Changed in version 3.10: Class methods now inherit the method
   attributes ("__module__", "__name__", "__qualname__", "__doc__" and
   "__annotations__") and have a new "__wrapped__" attribute.

   Changed in version 3.11: Class methods can no longer wrap other
   *descriptors* such as "property()".

compile(source, filename, mode, flags=0, dont_inherit=False, optimize=-1)

   Compile the *source* into a code or AST object.  Code objects can
   be executed by "exec()" or "eval()".  *source* can either be a
   normal string, a byte 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
   compiler options should be activated and which future features
   should be allowed. If neither is present (or both are zero) the
   code is compiled with the same flags that affect the code that is
   calling "compile()". If the *flags* argument is given and
   *dont_inherit* is not (or is zero) then the compiler options and
   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 flags
   (future features and compiler options) in the surrounding code are
   ignored.

   Compiler options and future statements are specified by bits which
   can be bitwise ORed together to specify multiple options. The
   bitfield required to specify a given future feature can be found as
   the "compiler_flag" attribute on the "_Feature" instance in the
   "__future__" module. Compiler flags can be found in "ast" module,
   with "PyCF_" prefix.

   The argument *optimize* specifies the optimization level of the
   compiler; the default value of "-1" selects the optimization level
   of the interpreter as given by "-O" options.  Explicit levels are
   "0" (no optimization; "__debug__" is true), "1" (asserts are
   removed, "__debug__" is false) or "2" (docstrings are removed too).

   This function raises "SyntaxError" if the compiled source is
   invalid, and "ValueError" if the source contains null bytes.

   If you want to parse Python code into its AST representation, see
   "ast.parse()".

   Raises an auditing event "compile" with arguments "source" and
   "filename". This event may also be raised by implicit compilation.

   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.

   Warning:

     It is possible to crash the Python interpreter with a
     sufficiently large/complex string when compiling to an AST object
     due to stack depth limitations in Python’s AST compiler.

   Changed in version 3.2: Allowed use of Windows and Mac newlines.
   Also, input in "'exec'" mode does not have to end in a newline
   anymore.  Added the *optimize* parameter.

   Changed in version 3.5: Previously, "TypeError" was raised when
   null bytes were encountered in *source*.

   Added in version 3.8: "ast.PyCF_ALLOW_TOP_LEVEL_AWAIT" can now be
   passed in flags to enable support for top-level "await", "async
   for", and "async with".

class complex(number=0, /)
class complex(string, /)
class complex(real=0, imag=0)

   Convert a single string or number to a complex number, or create a
   complex number from real and imaginary parts.

   Examples:

      >>> complex('+1.23')
      (1.23+0j)
      >>> complex('-4.5j')
      -4.5j
      >>> complex('-1.23+4.5j')
      (-1.23+4.5j)
      >>> complex('\t( -1.23+4.5J )\n')
      (-1.23+4.5j)
      >>> complex('-Infinity+NaNj')
      (-inf+nanj)
      >>> complex(1.23)
      (1.23+0j)
      >>> complex(imag=-4.5)
      -4.5j
      >>> complex(-1.23, 4.5)
      (-1.23+4.5j)

   If the argument is a string, it must contain either a real part (in
   the same format as for "float()") or an imaginary part (in the same
   format but with a "'j'" or "'J'" suffix), or both real and
   imaginary parts (the sign of the imaginary part is mandatory in
   this case). The string can optionally be surrounded by whitespaces
   and the round parentheses "'('" and "')'", which are ignored. The
   string must not contain whitespace between "'+'", "'-'", the "'j'"
   or "'J'" suffix, and the decimal number. For example,
   "complex('1+2j')" is fine, but "complex('1 + 2j')" raises
   "ValueError". More precisely, the input must conform to the
   "complexvalue" production rule in the following grammar, after
   parentheses and leading and trailing whitespace characters are
   removed:

      complexvalue ::= floatvalue |
                       floatvalue ("j" | "J") |
                       floatvalue sign absfloatvalue ("j" | "J")

   If the argument is a number, the constructor serves as a numeric
   conversion like "int" and "float". For a general Python object "x",
   "complex(x)" delegates to "x.__complex__()". If "__complex__()" is
   not defined then it falls back to "__float__()". If "__float__()"
   is not defined then it falls back to "__index__()".

   If two arguments are provided or keyword arguments are used, each
   argument may be any numeric type (including complex). If both
   arguments are real numbers, return a complex number with the real
   component *real* and the imaginary component *imag*. If both
   arguments are complex numbers, return a complex number with the
   real component "real.real-imag.imag" and the imaginary component
   "real.imag+imag.real". If one of arguments is a real number, only
   its real component is used in the above expressions.

   If all arguments are omitted, returns "0j".

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

   Changed in version 3.6: Grouping digits with underscores as in code
   literals is allowed.

   Changed in version 3.8: Falls back to "__index__()" if
   "__complex__()" and "__float__()" are not defined.

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". *name* need not be a Python
   identifier (see "setattr()").

class dict(**kwarg)
class dict(mapping, **kwarg)
class dict(iterable, **kwarg)

   Create a new dictionary.  The "dict" object is the dictionary
   class. See "dict" and Mapping Types — dict for documentation about
   this class.

   For other containers see the built-in "list", "set", and "tuple"
   classes, as well as the "collections" module.

dir()
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()   # show the names in the module namespace  
   ['__builtins__', '__name__', 'struct']
   >>> dir(struct)   # show the names in the struct module 
   ['Struct', '__all__', '__builtins__', '__cached__', '__doc__', '__file__',
    '__initializing__', '__loader__', '__name__', '__package__',
    '_clearcache', 'calcsize', 'error', 'pack', 'pack_into',
    'unpack', 'unpack_from']
   >>> class Shape:
   ...     def __dir__(self):
   ...         return ['area', 'perimeter', 'location']
   ...
   >>> s = Shape()
   >>> dir(s)
   ['area', 'location', 'perimeter']

   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 values obtained from iterating over *iterable*.

   >>> 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(iterable, start=0):
          n = start
          for elem in iterable:
              yield n, elem
              n += 1

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

   Parameters:
      * **expression** ("str" | code object) – A Python expression.

      * **globals** ("dict" | "None") – The global namespace (default:
        "None").

      * **locals** (*mapping* | "None") – The local namespace
        (default: "None").

   Returns:
      The result of the evaluated expression.

   Raises:
      Syntax errors are reported as exceptions.

   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 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 before
   *expression* is parsed.  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 "eval()".  If the
   *locals* dictionary is omitted it defaults to the *globals*
   dictionary.  If both dictionaries are omitted, the expression is
   executed with the *globals* and *locals* in the environment where
   "eval()" is called.  Note, *eval()* does not have access to the
   *nested scopes* (non-locals) in the enclosing environment.

   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 *mode* argument, "eval()"'s return value will
   be "None".

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

   If the given source is a string, then leading and trailing spaces
   and tabs are stripped.

   See "ast.literal_eval()" for a function that can safely evaluate
   strings with expressions containing only literals.

   Raises an auditing event "exec" with the code object as the
   argument. Code compilation events may also be raised.

exec(object, globals=None, locals=None, /, *, closure=None)

   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 "nonlocal",
   "yield",  and "return" 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 (and not a subclass of 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.  Remember that at the module level, globals and locals are
   the same dictionary.

   Note:

     Most users should just pass a *globals* argument and never
     *locals*. If exec gets two separate objects as *globals* and
     *locals*, the code will be executed as if it were embedded in a
     class definition.

   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()".

   The *closure* argument specifies a closure–a tuple of cellvars.
   It’s only valid when the *object* is a code object containing free
   variables. The length of the tuple must exactly match the number of
   free variables referenced by the code object.

   Raises an auditing event "exec" with the code object as the
   argument. Code compilation events may also be raised.

   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.

   Changed in version 3.11: Added the *closure* parameter.

filter(function, iterable)

   Construct an iterator from those elements of *iterable* for which
   *function* is 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* is false.

class float(number=0.0, /)
class float(string, /)

   Return a floating point number constructed from a number or a
   string.

   Examples:

      >>> float('+1.23')
      1.23
      >>> float('   -12345\n')
      -12345.0
      >>> float('1e-003')
      0.001
      >>> float('+1E6')
      1000000.0
      >>> float('-Infinity')
      -inf

   If the argument is a string, it should contain a decimal number,
   optionally preceded by a sign, and optionally embedded in
   whitespace.  The optional sign may be "'+'" or "'-'"; a "'+'" sign
   has no effect on the value produced.  The argument may also be a
   string representing a NaN (not-a-number), or positive or negative
   infinity. More precisely, the input must conform to the
   "floatvalue" production rule in the following grammar, after
   leading and trailing whitespace characters are removed:

      sign          ::= "+" | "-"
      infinity      ::= "Infinity" | "inf"
      nan           ::= "nan"
      digit         ::= <a Unicode decimal digit, i.e. characters in Unicode general category Nd>
      digitpart     ::= digit (["_"] digit)*
      number        ::= [digitpart] "." digitpart | digitpart ["."]
      exponent      ::= ("e" | "E") [sign] digitpart
      floatnumber   ::= number [exponent]
      absfloatvalue ::= floatnumber | infinity | nan
      floatvalue    ::= [sign] absfloatvalue

   Case is not significant, so, for example, “inf”, “Inf”, “INFINITY”,
   and “iNfINity” are all acceptable spellings for positive infinity.

   Otherwise, if the argument is an integer or a floating point
   number, a floating point number with the same value (within
   Python’s floating point precision) is returned.  If the argument is
   outside the range of a Python float, an "OverflowError" will be
   raised.

   For a general Python object "x", "float(x)" delegates to
   "x.__float__()".  If "__float__()" is not defined then it falls
   back to "__index__()".

   If no argument is given, "0.0" is returned.

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

   Changed in version 3.6: Grouping digits with underscores as in code
   literals is allowed.

   Changed in version 3.7: The parameter is now positional-only.

   Changed in version 3.8: Falls back to "__index__()" if
   "__float__()" is not defined.

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.

   The default *format_spec* is an empty string which usually gives
   the same effect as calling "str(value)".

   A call to "format(value, format_spec)" is translated to
   "type(value).__format__(value, format_spec)" which bypasses the
   instance dictionary when searching for the value’s "__format__()"
   method. A "TypeError" exception is raised if the method search
   reaches "object" and the *format_spec* is non-empty, or if either
   the *format_spec* or the return value are not strings.

   Changed in version 3.4: "object().__format__(format_spec)" raises
   "TypeError" if *format_spec* is not an empty string.

class frozenset(iterable=set())

   Return a new "frozenset" object, optionally with elements taken
   from *iterable*.  "frozenset" is a built-in class.  See "frozenset"
   and Set Types — set, frozenset for documentation about this class.

   For other containers see the built-in "set", "list", "tuple", and
   "dict" classes, as well as the "collections" module.

getattr(object, name)
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. *name* need not be
   a Python identifier (see "setattr()").

   Note:

     Since private name mangling happens at compilation time, one must
     manually mangle a private attribute’s (attributes with two
     leading underscores) name in order to retrieve it with
     "getattr()".

globals()

   Return the dictionary implementing the current module namespace.
   For code within functions, this is set when the function is defined
   and remains the same regardless of where the function 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 "AttributeError" 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).

   Note:

     For objects with custom "__hash__()" methods, note that "hash()"
     truncates the return value based on the bit width of the host
     machine.

help()
help(request)

   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.

   Note that if a slash(/) appears in the parameter list of a function
   when invoking "help()", it means that the parameters prior to the
   slash are positional-only. For more info, see the FAQ entry on
   positional-only parameters.

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

   Changed in version 3.4: Changes to "pydoc" and "inspect" mean that
   the reported signatures for callables are now more comprehensive
   and consistent.

hex(x)

   Convert an integer number to a lowercase hexadecimal string
   prefixed with “0x”. If *x* is not a Python "int" object, it has to
   define an "__index__()" method that returns an integer. Some
   examples:

   >>> hex(255)
   '0xff'
   >>> hex(-42)
   '-0x2a'

   If you want to convert an integer number to an uppercase or lower
   hexadecimal string with prefix or not, you can use either of the
   following ways:

   >>> '%#x' % 255, '%x' % 255, '%X' % 255
   ('0xff', 'ff', 'FF')
   >>> format(255, '#x'), format(255, 'x'), format(255, 'X')
   ('0xff', 'ff', 'FF')
   >>> f'{255:#x}', f'{255:x}', f'{255:X}'
   ('0xff', 'ff', 'FF')

   See also "format()" for more information.

   See also "int()" for converting a hexadecimal string to an integer
   using a base of 16.

   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 in memory.

   Raises an auditing event "builtins.id" with argument "id".

input()
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.

   Raises an auditing event "builtins.input" with argument "prompt"
   before reading input

   Raises an auditing event "builtins.input/result" with the result
   after successfully reading input.

class int(number=0, /)
class int(string, /, base=10)

   Return an integer object constructed from a number or a string, or
   return "0" if no arguments are given.

   Examples:

      >>> int(123.45)
      123
      >>> int('123')
      123
      >>> int('   -12_345\n')
      -12345
      >>> int('FACE', 16)
      64206
      >>> int('0xface', 0)
      64206
      >>> int('01110011', base=2)
      115

   If the argument defines "__int__()", "int(x)" returns
   "x.__int__()".  If the argument defines "__index__()", it returns
   "x.__index__()".  If the argument defines "__trunc__()", it returns
   "x.__trunc__()". For floating point numbers, this truncates towards
   zero.

   If the argument is not a number or if *base* is given, then it must
   be a string, "bytes", or "bytearray" instance representing an
   integer in radix *base*.  Optionally, the string can be preceded by
   "+" or "-" (with no space in between), have leading zeros, be
   surrounded by whitespace, and have single underscores interspersed
   between digits.

   A base-n integer string contains digits, each representing a value
   from 0 to n-1. The values 0–9 can be represented by any Unicode
   decimal digit. The values 10–35 can be represented by "a" to "z"
   (or "A" to "Z"). The default *base* is 10. The allowed bases are 0
   and 2–36. Base-2, -8, and -16 strings can be optionally prefixed
   with "0b"/"0B", "0o"/"0O", or "0x"/"0X", as with integer literals
   in code.  For base 0, the string is interpreted in a similar way to
   an integer literal in code, in that the actual base is 2, 8, 10, or
   16 as determined by the prefix. Base 0 also disallows leading
   zeros: "int('010', 0)" is not legal, while "int('010')" and
   "int('010', 8)" are.

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

   Changed in version 3.4: If *base* is not an instance of "int" and
   the *base* object has a "base.__index__" method, that method is
   called to obtain an integer for the base.  Previous versions used
   "base.__int__" instead of "base.__index__".

   Changed in version 3.6: Grouping digits with underscores as in code
   literals is allowed.

   Changed in version 3.7: The first parameter is now positional-only.

   Changed in version 3.8: Falls back to "__index__()" if "__int__()"
   is not defined.

   Changed in version 3.11: The delegation to "__trunc__()" is
   deprecated.

   Changed in version 3.11: "int" string inputs and string
   representations can be limited to help avoid denial of service
   attacks. A "ValueError" is raised when the limit is exceeded while
   converting a string to an "int" or when converting an "int" into a
   string would exceed the limit. See the integer string conversion
   length limitation documentation.

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.  If *object* is not an object of the given type,
   the function always returns "False". If *classinfo* is a tuple of
   type objects (or recursively, other such tuples) or a Union Type of
   multiple types, return "True" if *object* is an instance of any of
   the types. If *classinfo* is not a type or tuple of types and such
   tuples, a "TypeError" exception is raised. "TypeError" may not be
   raised for an invalid type if an earlier check succeeds.

   Changed in version 3.10: *classinfo* can be a Union Type.

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 (or
   recursively, other such tuples) or a Union Type, in which case
   return "True" if *class* is a subclass of any entry in *classinfo*.
   In any other case, a "TypeError" exception is raised.

   Changed in version 3.10: *classinfo* can be a Union Type.

iter(object)
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 *iterable* 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.

   See also Iterator Types.

   One useful application of the second form of "iter()" is to build a
   block-reader. For example, reading fixed-width blocks from a binary
   database file until the end of file is reached:

      from functools import partial
      with open('mydata.db', 'rb') as f:
          for block in iter(partial(f.read, 64), b''):
              process_block(block)

len(s)

   Return the length (the number of items) of an object.  The argument
   may be a sequence (such as a string, bytes, tuple, list, or range)
   or a collection (such as a dictionary, set, or frozen set).

   **CPython implementation detail:** "len" raises "OverflowError" on
   lengths larger than "sys.maxsize", such as "range(2 ** 100)".

class list
class list(iterable)

   Rather than being a function, "list" is actually a mutable sequence
   type, as documented in Lists and Sequence Types — 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 that at
   the module level, "locals()" and "globals()" are the same
   dictionary.

   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, *iterables)

   Return an iterator that applies *function* to every item of
   *iterable*, yielding the results.  If additional *iterables*
   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, *, key=None)
max(iterable, *, default, key=None)
max(arg1, arg2, *args, key=None)

   Return the largest item in an iterable or the largest of two or
   more arguments.

   If one positional argument is provided, it should be an *iterable*.
   The largest item in the iterable is returned.  If two or more
   positional arguments are provided, the largest of the positional
   arguments is returned.

   There are two optional keyword-only arguments. The *key* argument
   specifies a one-argument ordering function like that used for
   "list.sort()". The *default* argument specifies an object to return
   if the provided iterable is empty. If the iterable is empty and
   *default* is not provided, a "ValueError" is raised.

   If multiple items are maximal, the function returns the first one
   encountered.  This is consistent with other sort-stability
   preserving tools such as "sorted(iterable, key=keyfunc,
   reverse=True)[0]" and "heapq.nlargest(1, iterable, key=keyfunc)".

   Changed in version 3.4: Added the *default* keyword-only parameter.

   Changed in version 3.8: The *key* can be "None".

class memoryview(object)

   Return a “memory view” object created from the given argument.  See
   Memory Views for more information.

min(iterable, *, key=None)
min(iterable, *, default, key=None)
min(arg1, arg2, *args, key=None)

   Return the smallest item in an iterable or the smallest of two or
   more arguments.

   If one positional argument is provided, it should be an *iterable*.
   The smallest item in the iterable is returned.  If two or more
   positional arguments are provided, the smallest of the positional
   arguments is returned.

   There are two optional keyword-only arguments. The *key* argument
   specifies a one-argument ordering function like that used for
   "list.sort()". The *default* argument specifies an object to return
   if the provided iterable is empty. If the iterable is empty and
   *default* is not provided, a "ValueError" is raised.

   If multiple items are minimal, the function returns the first one
   encountered.  This is consistent with other sort-stability
   preserving tools such as "sorted(iterable, key=keyfunc)[0]" and
   "heapq.nsmallest(1, iterable, key=keyfunc)".

   Changed in version 3.4: Added the *default* keyword-only parameter.

   Changed in version 3.8: The *key* can be "None".

next(iterator)
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.

class object

   Return a new featureless object.  "object" is a base for all
   classes. It has 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 prefixed with “0o”.
   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. For example:

   >>> oct(8)
   '0o10'
   >>> oct(-56)
   '-0o70'

   If you want to convert an integer number to an octal string either
   with the prefix “0o” or not, you can use either of the following
   ways.

   >>> '%#o' % 10, '%o' % 10
   ('0o12', '12')
   >>> format(10, '#o'), format(10, 'o')
   ('0o12', '12')
   >>> f'{10:#o}', f'{10:o}'
   ('0o12', '12')

   See also "format()" for more information.

open(file, mode='r', buffering=-1, encoding=None, errors=None, newline=None, closefd=True, opener=None)

   Open *file* and return a corresponding *file object*.  If the file
   cannot be opened, an "OSError" is raised. See Reading and Writing
   Files for more examples of how to use this function.

   *file* is a *path-like object* giving the pathname (absolute or
   relative to 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.  It defaults to "'r'" which means open for reading
   in text mode. Other common values are "'w'" for writing (truncating
   the file if it already exists), "'x'" for exclusive creation, 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).  In text mode, if *encoding* is not specified the
   encoding used is platform-dependent: "locale.getencoding()" is
   called to get the current locale encoding. (For reading and writing
   raw bytes use binary mode and leave *encoding* unspecified.)  The
   available modes are:

   +-----------+-----------------------------------------------------------------+
   | Character | Meaning                                                         |
   |===========|=================================================================|
   | "'r'"     | open for reading (default)                                      |
   +-----------+-----------------------------------------------------------------+
   | "'w'"     | open for writing, truncating the file first                     |
   +-----------+-----------------------------------------------------------------+
   | "'x'"     | open for exclusive creation, failing if the file already exists |
   +-----------+-----------------------------------------------------------------+
   | "'a'"     | open for writing, appending to the end of file if it exists     |
   +-----------+-----------------------------------------------------------------+
   | "'b'"     | binary mode                                                     |
   +-----------+-----------------------------------------------------------------+
   | "'t'"     | text mode (default)                                             |
   +-----------+-----------------------------------------------------------------+
   | "'+'"     | open for updating (reading and writing)                         |
   +-----------+-----------------------------------------------------------------+

   The default mode is "'r'" (open for reading text, a synonym of
   "'rt'"). Modes "'w+'" and "'w+b'" open and truncate the file.
   Modes "'r+'" and "'r+b'" open the file with no truncation.

   As mentioned in the Overview, Python distinguishes between binary
   and text I/O.  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
   "str", the bytes having been first decoded using a platform-
   dependent encoding or using the specified *encoding* if given.

   Note:

     Python doesn’t depend on the underlying operating system’s notion
     of text files; all the processing is done by Python itself, and
     is therefore platform-independent.

   *buffering* is an optional integer used to set the buffering
   policy.  Pass 0 to switch buffering off (only allowed in binary
   mode), 1 to select line buffering (only usable when writing in text
   mode), and an integer > 1 to indicate the size in bytes of a fixed-
   size chunk buffer. Note that specifying a buffer size this way
   applies for binary buffered I/O, but "TextIOWrapper" (i.e., files
   opened with "mode='r+'") would have another buffering. To disable
   buffering in "TextIOWrapper", consider using the "write_through"
   flag for "io.TextIOWrapper.reconfigure()". When no *buffering*
   argument is given, the default buffering policy works as follows:

   * Binary files are buffered in fixed-size chunks; the size of the
     buffer is chosen using a heuristic trying to determine the
     underlying device’s “block size” and falling back on
     "io.DEFAULT_BUFFER_SIZE".  On many systems, the buffer will
     typically be 4096 or 8192 bytes long.

   * “Interactive” text files (files for which "isatty()" returns
     "True") use line buffering.  Other text files use the policy
     described above for binary files.

   *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.getencoding()" returns),
   but any *text 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. A variety of standard error handlers are available (listed
   under Error Handlers), though any error handling name that has been
   registered with "codecs.register_error()" is also valid.  The
   standard names include:

   * "'strict'" to raise a "ValueError" exception if there is an
     encoding error.  The default value of "None" has the same effect.

   * "'ignore'" ignores 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.

   * "'surrogateescape'" will represent any incorrect bytes as low
     surrogate code units ranging from U+DC80 to U+DCFF. These
     surrogate code units will then be turned back into the same bytes
     when the "surrogateescape" error handler is used when writing
     data.  This is useful for processing files in an unknown
     encoding.

   * "'xmlcharrefreplace'" is only supported when writing to a file.
     Characters not supported by the encoding are replaced with the
     appropriate XML character reference "&#*nnn*;".

   * "'backslashreplace'" replaces malformed data by Python’s
     backslashed escape sequences.

   * "'namereplace'" (also only supported when writing) replaces
     unsupported characters with "\N{...}" escape sequences.

   *newline* determines how to parse newline characters from the
   stream. It can be "None", "''", "'\n'", "'\r'", and "'\r\n'".  It
   works as follows:

   * When reading input from the stream, 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 newlines 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.

   * When writing output to the stream, if *newline* is "None", any
     "'\n'" characters written are translated to the system default
     line separator, "os.linesep".  If *newline* is "''" or "'\n'", 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*
   must be "True" (the default); otherwise, an error will be raised.

   A custom opener can be used by passing a callable as *opener*. The
   underlying file descriptor for the file object is then obtained by
   calling *opener* with (*file*, *flags*). *opener* must return an
   open file descriptor (passing "os.open" as *opener* results in
   functionality similar to passing "None").

   The newly created file is non-inheritable.

   The following example uses the dir_fd parameter of the "os.open()"
   function to open a file relative to a given directory:

      >>> import os
      >>> dir_fd = os.open('somedir', os.O_RDONLY)
      >>> def opener(path, flags):
      ...     return os.open(path, flags, dir_fd=dir_fd)
      ...
      >>> with open('spamspam.txt', 'w', opener=opener) as f:
      ...     print('This will be written to somedir/spamspam.txt', file=f)
      ...
      >>> os.close(dir_fd)  # don't leak a file descriptor

   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 an "io.BufferedReader"; in write binary and
   append binary modes, it returns an "io.BufferedWriter", and in
   read/write mode, it returns an "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".

   Raises an auditing event "open" with arguments "file", "mode",
   "flags".

   The "mode" and "flags" arguments may have been modified or inferred
   from the original call.

   Changed in version 3.3:

   * The *opener* parameter was added.

   * The "'x'" mode was added.

   * "IOError" used to be raised, it is now an alias of "OSError".

   * "FileExistsError" is now raised if the file opened in exclusive
     creation mode ("'x'") already exists.

   Changed in version 3.4:

   * The file is now non-inheritable.

   Changed in version 3.5:

   * If the system call is interrupted and the signal handler does not
     raise an exception, the function now retries the system call
     instead of raising an "InterruptedError" exception (see **PEP
     475** for the rationale).

   * The "'namereplace'" error handler was added.

   Changed in version 3.6:

   * Support added to accept objects implementing "os.PathLike".

   * On Windows, opening a console buffer may return a subclass of
     "io.RawIOBase" other than "io.FileIO".

   Changed in version 3.11: The "'U'" mode has been removed.

ord(c)

   Given a string representing one Unicode character, return an
   integer representing the Unicode code point of that character.  For
   example, "ord('a')" returns the integer "97" and "ord('€')" (Euro
   sign) returns "8364".  This is the inverse of "chr()".

pow(base, exp, mod=None)

   Return *base* to the power *exp*; if *mod* is present, return
   *base* to the power *exp*, modulo *mod* (computed more efficiently
   than "pow(base, exp) % mod"). The two-argument form "pow(base,
   exp)" is equivalent to using the power operator: "base**exp".

   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, "pow(10, 2)" returns "100", but "pow(10, -2)" returns
   "0.01".  For a negative base of type "int" or "float" and a non-
   integral exponent, a complex result is delivered.  For example,
   "pow(-9, 0.5)" returns a value close to "3j".

   For "int" operands *base* and *exp*, if *mod* is present, *mod*
   must also be of integer type and *mod* must be nonzero. If *mod* is
   present and *exp* is negative, *base* must be relatively prime to
   *mod*. In that case, "pow(inv_base, -exp, mod)" is returned, where
   *inv_base* is an inverse to *base* modulo *mod*.

   Here’s an example of computing an inverse for "38" modulo "97":

      >>> pow(38, -1, mod=97)
      23
      >>> 23 * 38 % 97 == 1
      True

   Changed in version 3.8: For "int" operands, the three-argument form
   of "pow" now allows the second argument to be negative, permitting
   computation of modular inverses.

   Changed in version 3.8: Allow keyword arguments.  Formerly, only
   positional arguments were supported.

print(*objects, sep=' ', end='\n', file=None, flush=False)

   Print *objects* to the text stream *file*, separated by *sep* and
   followed by *end*.  *sep*, *end*, *file*, and *flush*, 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 *objects* are
   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.
   Since printed arguments are converted to text strings, "print()"
   cannot be used with binary mode file objects.  For these, use
   "file.write(...)" instead.

   Output buffering is usually determined by *file*. However, if
   *flush* is true, the stream is forcibly flushed.

   Changed in version 3.3: Added the *flush* keyword argument.

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

   Return a property attribute.

   *fget* is a function for getting an attribute value.  *fset* is a
   function for setting an attribute value. *fdel* is a function for
   deleting an attribute value.  And *doc* creates a docstring for the
   attribute.

   A typical use is to define a managed attribute "x":

      class C:
          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 *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:
          def __init__(self):
              self._voltage = 100000

          @property
          def voltage(self):
              """Get the current voltage."""
              return self._voltage

   The "@property" decorator turns the "voltage()" method into a
   “getter” for a read-only attribute with the same name, and it sets
   the docstring for *voltage* to “Get the current voltage.”

   @getter

   @setter

   @deleter

      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:
             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 object also has the attributes "fget",
      "fset", and "fdel" corresponding to the constructor arguments.

   Changed in version 3.5: The docstrings of property objects are now
   writeable.

class range(stop)
class range(start, stop, step=1)

   Rather than being a function, "range" is actually an immutable
   sequence type, as documented in Ranges and Sequence Types — list,
   tuple, range.

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. If
   "sys.displayhook()" is not accessible, this function will raise
   "RuntimeError".

   This class has a custom representation that can be evaluated:

      class Person:
         def __init__(self, name, age):
            self.name = name
            self.age = age

         def __repr__(self):
            return f"Person('{self.name}', {self.age})"

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(number, ndigits=None)

   Return *number* rounded to *ndigits* precision after the decimal
   point.  If *ndigits* is omitted or is "None", it returns the
   nearest integer to its input.

   For the built-in types supporting "round()", values are rounded to
   the closest multiple of 10 to the power minus *ndigits*; 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").  Any integer value is valid for
   *ndigits* (positive, zero, or negative).  The return value is an
   integer if *ndigits* is omitted or "None". Otherwise, the return
   value has the same type as *number*.

   For a general Python object "number", "round" delegates to
   "number.__round__".

   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.

class set
class set(iterable)

   Return a new "set" object, optionally with elements taken from
   *iterable*.  "set" is a built-in class.  See "set" and Set Types —
   set, frozenset for documentation about this class.

   For other containers see the built-in "frozenset", "list", "tuple",
   and "dict" classes, as well as the "collections" module.

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".

   *name* need not be a Python identifier as defined in Identifiers
   and keywords unless the object chooses to enforce that, for example
   in a custom "__getattribute__()" or via "__slots__". An attribute
   whose name is not an identifier will not be accessible using the
   dot notation, but is accessible through "getattr()" etc..

   Note:

     Since private name mangling happens at compilation time, one must
     manually mangle a private attribute’s (attributes with two
     leading underscores) name in order to set it with "setattr()".

class slice(stop)
class slice(start, stop, step=None)

   Return a *slice* object representing the set of indices specified
   by "range(start, stop, step)".  The *start* and *step* arguments
   default to "None".

   start

   stop

   step

      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 NumPy and other third-party packages.

   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*.

   Changed in version 3.12: Slice objects are now *hashable* (provided
   "start", "stop", and "step" are hashable).

sorted(iterable, /, *, key=None, reverse=False)

   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 element in *iterable* (for example,
   "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.

   Use "functools.cmp_to_key()" to convert an old-style *cmp* function
   to a *key* function.

   The built-in "sorted()" function is guaranteed to be stable. A sort
   is stable if it guarantees not to change the relative order of
   elements that compare equal — this is helpful for sorting in
   multiple passes (for example, sort by department, then by salary
   grade).

   The sort algorithm uses only "<" comparisons between items.  While
   defining an "__lt__()" method will suffice for sorting, **PEP 8**
   recommends that all six rich comparisons be implemented.  This will
   help avoid bugs when using the same data with other ordering tools
   such as "max()" that rely on a different underlying method.
   Implementing all six comparisons also helps avoid confusion for
   mixed type comparisons which can call reflected the "__gt__()"
   method.

   For sorting examples and a brief sorting tutorial, see Sorting
   Techniques.

@staticmethod

   Transform a method into a static method.

   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, argN): ...

   The "@staticmethod" form is a function *decorator* – see Function
   definitions for details.

   A static method can be called either on the class (such as "C.f()")
   or on an instance (such as "C().f()"). Moreover, the static method
   *descriptor* is also callable, so it can be used in the class
   definition (such as "f()").

   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.

   Like all decorators, it is also possible to call "staticmethod" as
   a regular function and do something with its result.  This is
   needed in some cases where you need a reference to a function from
   a class body and you want to avoid the automatic transformation to
   instance method.  For these cases, use this idiom:

      def regular_function():
          ...

      class C:
          method = staticmethod(regular_function)

   For more information on static methods, see The standard type
   hierarchy.

   Changed in version 3.10: Static methods now inherit the method
   attributes ("__module__", "__name__", "__qualname__", "__doc__" and
   "__annotations__"), have a new "__wrapped__" attribute, and are now
   callable as regular functions.

class str(object='')
class str(object=b'', encoding='utf-8', errors='strict')

   Return a "str" version of *object*.  See "str()" for details.

   "str" is the built-in string *class*.  For general information
   about strings, see Text Sequence Type — str.

sum(iterable, /, start=0)

   Sums *start* and the items of an *iterable* from left to right and
   returns the total.  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()".

   Changed in version 3.8: The *start* parameter can be specified as a
   keyword argument.

   Changed in version 3.12: Summation of floats switched to an
   algorithm that gives higher accuracy on most builds.

class super
class super(type, object_or_type=None)

   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 *object_or_type* determines the *method resolution order* to be
   searched.  The search starts from the class right after the *type*.

   For example, if "__mro__" of *object_or_type* is "D -> B -> C -> A
   -> object" and the value of *type* is "B", then "super()" searches
   "C -> A -> object".

   The "__mro__" attribute of the *object_or_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 such
   implementations 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)

   In addition to method lookups, "super()" also works for attribute
   lookups.  One possible use case for this is calling *descriptors*
   in a parent or sibling class.

   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, aside from the zero argument form, "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 only works inside a class definition, as the compiler
   fills in the necessary details to correctly retrieve the class
   being defined, as well as accessing the current instance for
   ordinary methods.

   For practical suggestions on how to design cooperative classes
   using "super()", see guide to using super().

class tuple
class tuple(iterable)

   Rather than being a function, "tuple" is actually an immutable
   sequence type, as documented in Tuples and Sequence Types — list,
   tuple, range.

class type(object)
class type(name, bases, dict, **kwds)

   With one argument, 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, 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 contains the base classes and becomes the "__bases__"
   attribute; if empty, "object", the ultimate base of all classes, is
   added.  The *dict* dictionary contains attribute and method
   definitions for the class body; it may be copied or wrapped before
   becoming the "__dict__" attribute. The following two statements
   create identical "type" objects:

   >>> class X:
   ...     a = 1
   ...
   >>> X = type('X', (), dict(a=1))

   See also Type Objects.

   Keyword arguments provided to the three argument form are passed to
   the appropriate metaclass machinery (usually "__init_subclass__()")
   in the same way that keywords in a class definition (besides
   *metaclass*) would.

   See also Customizing class creation.

   Changed in version 3.6: Subclasses of "type" which don’t override
   "type.__new__" may no longer use the one-argument form to get the
   type of an object.

vars()
vars(object)

   Return the "__dict__" attribute for a module, class, instance, or
   any other object with a "__dict__" attribute.

   Objects such as modules and instances have an updateable "__dict__"
   attribute; however, other objects may have write restrictions on
   their "__dict__" attributes (for example, classes use a
   "types.MappingProxyType" to prevent direct dictionary updates).

   Without an argument, "vars()" acts like "locals()".  Note, the
   locals dictionary is only useful for reads since updates to the
   locals dictionary are ignored.

   A "TypeError" exception is raised if an object is specified but it
   doesn’t have a "__dict__" attribute (for example, if its class
   defines the "__slots__" attribute).

zip(*iterables, strict=False)

   Iterate over several iterables in parallel, producing tuples with
   an item from each one.

   Example:

      >>> for item in zip([1, 2, 3], ['sugar', 'spice', 'everything nice']):
      ...     print(item)
      ...
      (1, 'sugar')
      (2, 'spice')
      (3, 'everything nice')

   More formally: "zip()" returns an iterator of tuples, where the
   *i*-th tuple contains the *i*-th element from each of the argument
   iterables.

   Another way to think of "zip()" is that it turns rows into columns,
   and columns into rows.  This is similar to transposing a matrix.

   "zip()" is lazy: The elements won’t be processed until the iterable
   is iterated on, e.g. by a "for" loop or by wrapping in a "list".

   One thing to consider is that the iterables passed to "zip()" could
   have different lengths; sometimes by design, and sometimes because
   of a bug in the code that prepared these iterables.  Python offers
   three different approaches to dealing with this issue:

   * By default, "zip()" stops when the shortest iterable is
     exhausted. It will ignore the remaining items in the longer
     iterables, cutting off the result to the length of the shortest
     iterable:

        >>> list(zip(range(3), ['fee', 'fi', 'fo', 'fum']))
        [(0, 'fee'), (1, 'fi'), (2, 'fo')]

   * "zip()" is often used in cases where the iterables are assumed to
     be of equal length.  In such cases, it’s recommended to use the
     "strict=True" option. Its output is the same as regular "zip()":

        >>> list(zip(('a', 'b', 'c'), (1, 2, 3), strict=True))
        [('a', 1), ('b', 2), ('c', 3)]

     Unlike the default behavior, it raises a "ValueError" if one
     iterable is exhausted before the others:

     >>> for item in zip(range(3), ['fee', 'fi', 'fo', 'fum'], strict=True):  
     ...     print(item)
     ...
     (0, 'fee')
     (1, 'fi')
     (2, 'fo')
     Traceback (most recent call last):
       ...
     ValueError: zip() argument 2 is longer than argument 1

     Without the "strict=True" argument, any bug that results in
     iterables of different lengths will be silenced, possibly
     manifesting as a hard-to-find bug in another part of the program.

   * Shorter iterables can be padded with a constant value to make all
     the iterables have the same length.  This is done by
     "itertools.zip_longest()".

   Edge cases: With a single iterable argument, "zip()" returns an
   iterator of 1-tuples.  With no arguments, it returns an empty
   iterator.

   Tips and tricks:

   * 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,
     strict=True)".  This repeats the *same* iterator "n" times so
     that each output tuple has the result of "n" calls to the
     iterator. This has the effect of dividing the input into n-length
     chunks.

   * "zip()" in conjunction with the "*" operator can be used to unzip
     a list:

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

   Changed in version 3.10: Added the "strict" argument.

__import__(name, globals=None, locals=None, fromlist=(), level=0)

   Note:

     This is an advanced function that is not needed in everyday
     Python programming, unlike "importlib.import_module()".

   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 doing so is **strongly** discouraged as it is
   usually simpler to use import hooks (see **PEP 302**) to attain the
   same goals and does not cause issues with code which assumes the
   default import implementation is in use.  Direct use of
   "__import__()" is also discouraged in favor of
   "importlib.import_module()".

   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__()" (see
   **PEP 328** for the details).

   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, use "importlib.import_module()".

   Changed in version 3.3: Negative values for *level* are no longer
   supported (which also changes the default value to 0).

   Changed in version 3.9: When the command line options "-E" or "-I"
   are being used, the environment variable "PYTHONCASEOK" is now
   ignored.

-[ 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.
