The Python interpreter has a number of functions and types built into it that are always available. They are listed here in alphabetical order.
abs(x)__abs__(), abs(x) returns x.__abs__().all(iterable)Return True if all elements of the iterable are true (or if the iterable
is empty). Equivalent to:
def all(iterable):
for element in iterable:
if not element:
return False
return True
any(iterable)Return True if any element of the iterable is true. If the iterable
is empty, return False. Equivalent to:
def any(iterable):
for element in iterable:
if element:
return True
return False
ascii(object)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 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.
bool([x])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.
Raises an auditing event builtins.breakpoint with argument breakpointhook.
New in version 3.7.
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.
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.
@classmethodTransform a method into a class method.
A class method receives the class as implicit first argument, just like an instance method receives the instance. To declare a class method, use this idiom:
class C:
@classmethod
def f(cls, arg1, arg2, ...): ...
The @classmethod form is a function decorator – see
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().
For more information on class methods, see The standard type hierarchy.
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 future
statements affect the compilation of source. If neither
is present (or both are zero) the code is compiled with those future
statements that are in effect in the code that is calling compile(). If the
flags argument is given and dont_inherit is not (or is zero) then the
future statements specified by the flags argument are used in addition to
those that would be used anyway. If dont_inherit is a non-zero integer then
the flags argument is it – the future statements in effect around the call
to compile are ignored.
Future statements are specified by bits which can be bitwise ORed together to
specify multiple statements. The bitfield required to specify a given feature
can be found as the compiler_flag attribute on
the _Feature instance in the __future__ module.
The optional argument flags also controls whether the compiled source is
allowed to contain top-level await, async for and async with.
When the bit ast.PyCF_ALLOW_TOP_LEVEL_AWAIT is set, the return code
object has CO_COROUTINE set in co_code, and can be interactively
executed via await eval(code_object).
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.
complex([real[, imag]])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)setattr(). The arguments are an object and a string. The string must be the name of one of the object’s attributes. The function deletes the named attribute, provided the object allows it. For example, delattr(x, 'foobar') is equivalent to del x.foobar.
dict(**kwarg)dict(mapping, **kwarg)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([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)(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(sequence, start=0):
n = start
for elem in sequence:
yield n, elem
n += 1
eval(expression[, globals[, locals]])The arguments are a string and optional globals and locals. If provided, globals must be a dictionary. If provided, locals can be any mapping object.
The expression argument is parsed and evaluated as a Python expression
(technically speaking, a condition list) using the globals and locals
dictionaries as global and local namespace. If the globals dictionary is
present and 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. This means that
expression normally has full access to the standard builtins
module and restricted environments are propagated. If the locals
dictionary is omitted it defaults to the globals dictionary. If both
dictionaries are omitted, the expression is executed 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
returns the current global and local dictionary, respectively, which may be
useful to pass around for use by eval() or exec().
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[, locals]])This function supports dynamic execution of Python code. object must be
either a string or a code object. If it is a string, the string is parsed as
a suite of Python statements which is then executed (unless a syntax error
occurs). 1 If it is a code object, it is simply executed. In all cases,
the code that’s executed is expected to be valid as file input (see the
section “File input” in the Reference Manual). Be aware that the
return and yield statements may not be used outside of
function definitions even within the context of code passed to the
exec() function. The return value is None.
In all cases, if the optional parts are omitted, the code is executed in the current scope. If only globals is provided, it must be a dictionary (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 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().
Raises an auditing event exec with the code object
as the argument. Code compilation events may also be raised.
filter(function, iterable)Construct an iterator from those elements of iterable for which function
returns true. iterable may be either a sequence, a container which
supports iteration, or an iterator. If function is None, the identity
function is assumed, that is, all elements of iterable that are false are
removed.
Note that filter(function, iterable) is equivalent to the generator
expression (item for item in iterable if function(item)) if function is
not None and (item for item in iterable if item) if function is
None.
See itertools.filterfalse() for the complementary function that returns
elements of iterable for which function returns false.
float([x])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 a positive or negative infinity. More precisely, the
input must conform to the following grammar after leading and trailing
whitespace characters are removed:
sign ::= "+" | "-" infinity ::= "Infinity" | "inf" nan ::= "nan" numeric_value ::= floatnumber | infinity | nan numeric_string ::= [sign] numeric_value
Here floatnumber is the form of a Python floating-point literal,
described in Floating point literals. 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.
frozenset([iterable])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[, default])getattr(x, 'foobar') is equivalent to x.foobar. If the named attribute does not exist, default is returned if provided, otherwise AttributeError is raised.globals()hasattr(object, name)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([object])Invoke the built-in help system. (This function is intended for interactive use.) If no argument is given, the interactive help system starts on the interpreter console. If the argument is a string, then the string is looked up as the name of a module, function, class, method, keyword, or documentation topic, and a help page is printed on the console. If the argument is any other kind of object, a help page on the object is generated.
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.
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([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.
int([x])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
literal in radix base. Optionally, the literal can be
preceded by + or - (with no space in between) and surrounded by
whitespace. A base-n literal consists of the digits 0 to n-1, with a
to z (or A to Z) having
values 10 to 35. The default base is 10. The allowed values are 0 and 2–36.
Base-2, -8, and -16 literals can be optionally prefixed with 0b/0B,
0o/0O, or 0x/0X, as with integer literals in code. Base 0
means to interpret exactly as a code literal, so that the actual base is 2,
8, 10, or 16, and so that int('010', 0) is not legal, while
int('010') is, as well as int('010', 8).
The integer type is described in Numeric Types — int, float, complex.
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.
isinstance(object, classinfo)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), 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.issubclass(class, classinfo)True if class is a subclass (direct, indirect or virtual) of classinfo. A class is considered a subclass of itself. classinfo may be a tuple of class objects, in which case every entry in classinfo will be checked. In any other case, a TypeError exception is raised.iter(object[, sentinel])Return an iterator object. The first argument is interpreted very
differently depending on the presence of the second argument. Without a
second argument, object must be a collection object which supports the
iteration protocol (the __iter__() method), or it must support the
sequence protocol (the __getitem__() method with integer arguments
starting at 0). If it does not support either of those protocols,
TypeError is raised. If the second argument, sentinel, is given,
then object must be a callable object. The iterator created in this case
will call object with no arguments for each call to its
__next__() method; if the value returned is equal to
sentinel, StopIteration will be raised, otherwise the value will
be returned.
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)
list([iterable])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, ...)itertools.starmap().max(iterable, *[, key, default])max(arg1, arg2, *args[, key])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.
memoryview(obj)min(iterable, *[, key, default])min(arg1, arg2, *args[, key])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[, default])__next__() method. If default is given, it is returned if the iterator is exhausted, otherwise StopIteration is raised.objectReturn a new featureless object. object is a base for all classes.
It has the methods that are common to all instances of Python classes. This
function does not accept any arguments.
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 octal string either with 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.getpreferredencoding(False) 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 |
|---|---|
|
open for reading (default) |
|
open for writing, truncating the file first |
|
open for exclusive creation, failing if the file already exists |
|
open for writing, appending to the end of the file if it exists |
|
binary mode |
|
text mode (default) |
|
open for updating (reading and writing) |
The default mode is 'r' (open for reading text, 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.
There is an additional mode character permitted, 'U', which no longer
has any effect, and is considered deprecated. It previously enabled
universal newlines in text mode, which became the default behaviour
in Python 3.0. Refer to the documentation of the
newline parameter for further details.
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. 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.getpreferredencoding() 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 code
points in the Unicode Private Use Area ranging from U+DC80 to
U+DCFF. These private code points 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 controls how universal newlines mode works (it only
applies to text mode). 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.
FileExistsErroris now raised if the file opened in exclusive creation mode ('x') already exists.
Changed in version 3.4:
The file is now non-inheritable.
Deprecated since version 3.4, will be removed in version 3.9: The 'U' mode.
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
InterruptedErrorexception (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.RawIOBaseother thanio.FileIO.
ord(c)ord('a') returns the integer 97 and ord('€') (Euro sign) returns 8364. This is the inverse of chr().pow(base, exp[, mod])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, 10**2
returns 100, but 10**-2 returns 0.01.
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=sys.stdout, 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 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.
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.
range(stop)class range(start, stop[, step])
range is actually an immutable sequence type, as documented in Ranges and Sequence Types — list, tuple, range.repr(object)eval(), otherwise the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object. A class can control what this function returns for its instances by defining a __repr__() method.reversed(seq)__reversed__() method or supports the sequence protocol (the __len__() method and the __getitem__() method with integer arguments starting at 0).round(number[, ndigits])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.
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)getattr(). The arguments are an object, a string and an arbitrary value. The string may name an existing attribute or a new attribute. The function assigns the value to the attribute, provided the object allows it. For example, setattr(x, 'foobar', 123) is equivalent to x.foobar = 123.slice(stop)class slice(start, stop[, step])
range(start, stop, step). The start and step arguments default to None. Slice objects have read-only data attributes start, stop and step which merely return the argument values (or their default). They have no other explicit functionality; however they are used by Numerical Python and other third party extensions. Slice objects are also generated when extended indexing syntax is used. For example: a[start:stop:step] or a[start:stop, i]. See itertools.islice() for an alternate version that returns an iterator.sorted(iterable, *, key=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).
For sorting examples and a brief sorting tutorial, see Sorting HOW TO.
@staticmethodTransform 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()).
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:
class C:
builtin_open = staticmethod(open)
For more information on static methods, see The standard type hierarchy.
str(object='')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.
super([type[, object-or-type]])Return a proxy object that delegates method calls to a parent or sibling class of type. This is useful for accessing inherited methods that have been overridden in a class.
The 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 this method have the same calling signature in every case (because the order of calls is determined at runtime, because that order adapts to changes in the class hierarchy, and because that order can include sibling classes that are unknown prior to runtime).
For both use cases, a typical superclass call looks like this:
class C(B):
def method(self, arg):
super().method(arg) # This does the same thing as:
# super(C, self).method(arg)
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().
tuple([iterable])tuple is actually an immutable sequence type, as documented in Tuples and Sequence Types — list, tuple, range.type(object)type(name, bases, dict)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 itemizes the base classes and becomes the __bases__
attribute; and the dict dictionary is the namespace containing definitions
for class body and is copied to a standard dictionary to become the
__dict__ attribute. For example, the following two
statements create identical type objects:
>>> class X:
... a = 1
...
>>> X = type('X', (object,), dict(a=1))
See also Type Objects.
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([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)Make an iterator that aggregates elements from each of the iterables.
Returns an iterator of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. The iterator stops when the shortest input iterable is exhausted. With a single iterable argument, it returns an iterator of 1-tuples. With no arguments, it returns an empty iterator. Equivalent to:
def zip(*iterables):
# zip('ABCD', 'xy') --> Ax By
sentinel = object()
iterators = [iter(it) for it in iterables]
while iterators:
result = []
for it in iterators:
elem = next(it, sentinel)
if elem is sentinel:
return
result.append(elem)
yield tuple(result)
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). 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() should only be used with unequal length inputs when you don’t
care about trailing, unmatched values from the longer iterables. If those
values are important, use itertools.zip_longest() instead.
zip() in conjunction with the * operator can be used to unzip a
list:
>>> x = [1, 2, 3]
>>> y = [4, 5, 6]
>>> zipped = zip(x, y)
>>> list(zipped)
[(1, 4), (2, 5), (3, 6)]
>>> x2, y2 = zip(*zip(x, y))
>>> x == list(x2) and y == list(y2)
True
__import__(name, globals=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).
Footnotes