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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()
all()
any()
anext()
ascii()


B
bin()
bool()
breakpoint()
bytearray()
bytes()


C
callable()
chr()
classmethod()
compile()
complex()


D
delattr()
dict()
dir()
divmod()


E
enumerate()
eval()
exec()


F
filter()
float()
format()
frozenset()


G
getattr()
globals()


H
hasattr()
hash()
help()
hex()


I
id()
input()
int()
isinstance()
issubclass()
iter()
L
len()
list()
locals()


M
map()
max()
memoryview()
min()


N
next()


O
object()
oct()
open()
ord()


P
pow()
print()
property()








R
range()
repr()
reversed()
round()


S
set()
setattr()
slice()
sorted()
staticmethod()
str()
sum()
super()


T
tuple()
type()


V
vars()


Z
zip()


_
__import__()

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.

New 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.

New 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(x=False)¶

Return a Boolean value, i.e. one of True or False. x is converted using the
standard truth testing procedure. If x 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 Values).

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

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.

Raises an auditing event builtins.breakpoint with argument breakpointhook.

New 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.

New 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.

New 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(real=0, imag=0)¶ class complex(string)

Return a complex number with the value real + imag*1j 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 constructor serves as a numeric conversion like int and float. If both
arguments are omitted, returns 0j.

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__().

Note

When converting from a string, the string must not contain whitespace around the
central + or - operator. For example, complex('1+2j') is fine, but complex('1 +
2j') raises ValueError.

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)¶

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 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.

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 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.
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 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.

class float(x=0.0)¶

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

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"
digitpart   ::=  digit (["_"] digit)*
number      ::=  [digitpart] "." digitpart | digitpart ["."]
exponent    ::=  ("e" | "E") ["+" | "-"] digitpart
floatnumber ::=  number [exponent]
floatvalue  ::=  [sign] (floatnumber | infinity | nan)


Here digit is a Unicode decimal digit (character in the Unicode general category
Nd). 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.

Examples:

>>>

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


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: x is now a positional-only parameter.

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. See __hash__() for
details.

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(x=0)¶ class int(x, base=10)

Return an integer object constructed from a number or string x, or return 0 if
no arguments are given. If x defines __int__(), int(x) returns x.__int__(). If x
defines __index__(), it returns x.__index__(). If x defines __trunc__(), it
returns x.__trunc__(). For floating point numbers, this truncates towards zero.

If x is not a number or if base is given, then x 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: x is now a positional-only parameter.

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 x 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).

New in version 3.4: The default keyword-only argument.

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).

New in version 3.4: The default keyword-only argument.

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 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.

Whether the output is buffered is usually determined by file, but if the flush
keyword argument 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.”

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.

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=1)

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 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.

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 HOW TO.

@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, ...): ...


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, they can be called as regular functions
(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.

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.



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