Library Reference
While The Python Language Reference describes the exact syntax and semantics of the Python language, this library reference manual describes the standard library that is distributed with Python. It also describes some of the optional components that are commonly included in Python distributions.
Python’s standard library is very extensive, offering a wide range of facilities as indicated by the long table of contents listed below. The library contains built-in modules (written in C) that provide access to system functionality such as file I/O that would otherwise be inaccessible to Python programmers, as well as modules written in Python that provide standardized solutions for many problems that occur in everyday programming. Some of these modules are explicitly designed to encourage and enhance the portability of Python programs by abstracting away platform-specifics into platform-neutral APIs.
The Python installers for the Windows platform usually include the entire standard library and often also include many additional components. For Unix-like operating systems Python is normally provided as a collection of packages, so it may be necessary to use the packaging tools provided with the operating system to obtain some or all of the optional components.
In addition to the standard library, there is a growing collection of several thousand components (from individual programs and modules to packages and entire application development frameworks), available from the Python Package Index.
Introduction
The “Python library” contains several different kinds of components.
It contains data types that would normally be considered part of the “core” of a language, such as numbers and lists. For these types, the Python language core defines the form of literals and places some constraints on their semantics, but does not fully define the semantics. (On the other hand, the language core does define syntactic properties like the spelling and priorities of operators.)
The library also contains built-in functions and exceptions — objects that can be used by all Python code without the need of an import
statement. Some of these are defined by the core language, but many are not essential for the core semantics and are only described here.
The bulk of the library, however, consists of a collection of modules. There are many ways to dissect this collection. Some modules are written in C and built in to the Python interpreter; others are written in Python and imported in source form. Some modules provide interfaces that are highly specific to Python, like printing a stack trace; some provide interfaces that are specific to particular operating systems, such as access to specific hardware; others provide interfaces that are specific to a particular application domain, like the World Wide Web. Some modules are available in all versions and ports of Python; others are only available when the underlying system supports or requires them; yet others are available only when a particular configuration option was chosen at the time when Python was compiled and installed.
This manual is organized “from the inside out:” it first describes the built-in functions, data types and exceptions, and finally the modules, grouped in chapters of related modules.
This means that if you start reading this manual from the start, and skip to the next chapter when you get bored, you will get a reasonable overview of the available modules and application areas that are supported by the Python library. Of course, you don’t have to read it like a novel — you can also browse the table of contents (in front of the manual), or look for a specific function, module or term in the index (in the back). And finally, if you enjoy learning about random subjects, you choose a random page number (see module random
) and read a section or two. Regardless of the order in which you read the sections of this manual, it helps to start with chapter Built-in Functions, as the remainder of the manual assumes familiarity with this material.
Let the show begin!
Notes on availability
An “Availability: Unix” note means that this function is commonly found on Unix systems. It does not make any claims about its existence on a specific operating system.
If not separately noted, all functions that claim “Availability: Unix” are supported on macOS, which builds on a Unix core.
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 | |||
---|---|---|---|
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[, 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, otherwiseStopAsyncIteration
is raised.New in version 3.10.
any
(iterable)Return
True
if any element of the iterable is true. If the iterable is empty, returnFalse
. 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 byrepr()
using\x
,\u
, or\U
escapes. This generates a string similar to that returned byrepr()
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]) Return a Boolean value, i.e. one of
True
orFalse
. x is converted using the standard truth testing procedure. If x is false or omitted, this returnsFalse
; otherwise, it returnsTrue
. Thebool
class is a subclass ofint
(see Numeric Types — int, float, complex). It cannot be subclassed further. Its only instances areFalse
andTrue
(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()
, passingargs
andkws
straight through. By default,sys.breakpointhook()
callspdb.set_trace()
expecting no arguments. In this case, it is purely a convenience function so you don’t have to explicitly importpdb
or type as much code to enter the debugger. However,sys.breakpointhook()
can be set to some other function andbreakpoint()
will automatically call that, allowing you to drop into the debugger of choice.Raises an auditing event
builtins.breakpoint
with argumentbreakpointhook
.New in version 3.7.
- 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 thebytes
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 usingstr.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[, 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 ofbytearray
– 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 returnsTrue
, it is still possible that a call fails, but if it isFalse
, 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'
, whilechr(8364)
returns the string'€'
. This is the inverse oford()
.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 asC().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.
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()
oreval()
. source can either be a normal string, a byte string, or an AST object. Refer to theast
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 (
''
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 thanNone
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 inast
module, withPyCF_
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 are0
(no optimization;__debug__
is true),1
(asserts are removed,__debug__
is false) or2
(docstrings are removed too).This function raises
SyntaxError
if the compiled source is invalid, andValueError
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 argumentssource
andfilename
. 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 thecode
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-levelawait
,async for
, andasync with
.
- class
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
andfloat
. If both arguments are omitted, returns0j
.For a general Python object
x
,complex(x)
delegates tox.__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, butcomplex('1 + 2j')
raisesValueError
.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 todel x.foobar
.
- class
dict
(**kwarg) - class
dict
(mapping, **kwarg) - class
dict
(iterable, **kwarg) Create a new dictionary. The
dict
object is the dictionary class. Seedict
and Mapping Types — dict for documentation about this class.For other containers see the built-in
list
,set
, andtuple
classes, as well as thecollections
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 waydir()
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 usuallymath.floor(a / b)
but may be 1 less than that. In any caseq * b + a % b
is very close to a, ifa % b
is non-zero it has the same sign as b, and0 <= 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 byenumerate()
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 modulebuiltins
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 toeval()
. 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 whereeval()
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 beNone
.Hints: dynamic execution of statements is supported by the
exec()
function. Theglobals()
andlocals()
functions return the current global and local dictionary, respectively, which may be useful to pass around for use byeval()
orexec()
.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[, 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
nonlocal
,yield
, andreturn
statements may not be used outside of function definitions even within the context of code passed to theexec()
function. The return value isNone
.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 modulebuiltins
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 toexec()
.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 notNone
and(item for item in iterable if item)
if function isNone
.See
itertools.filterfalse()
for the complementary function that returns elements of iterable for which function returns false.
- class
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 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 tox.__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 totype(value).__format__(value, format_spec)
which bypasses the instance dictionary when searching for the value’s__format__()
method. ATypeError
exception is raised if the method search reachesobject
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)
raisesTypeError
if format_spec is not an empty string.
- class
frozenset
([iterable]) Return a new
frozenset
object, optionally with elements taken from iterable.frozenset
is a built-in class. Seefrozenset
and Set Types — set, frozenset for documentation about this class.For other containers see the built-in
set
,list
,tuple
, anddict
classes, as well as thecollections
module.
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 tox.foobar
. If the named attribute does not exist, default is returned if provided, otherwiseAttributeError
is raised.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 callinggetattr(object, name)
and seeing whether it raises anAttributeError
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 thathash()
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 argumentid
.
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, theninput()
will use it to provide elaborate line editing and history features.Raises an auditing event
builtins.input
with argumentprompt
before reading inputRaises an auditing event
builtins.input/result
with the result after successfully reading input.
- class
int
([x]) - 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)
returnsx.__int__()
. If x defines__index__()
, it returnsx.__index__()
. If x defines__trunc__()
, it returnsx.__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
, orbytearray
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, witha
toz
(orA
toZ
) 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 with0b
/0B
,0o
/0O
, or0x
/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 thatint('010', 0)
is not legal, whileint('010')
is, as well asint('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 abase.__index__
method, that method is called to obtain an integer for the base. Previous versions usedbase.__int__
instead ofbase.__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)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 returnsFalse
. If classinfo is a tuple of type objects (or recursively, other such tuples) or a Union Type of multiple types, returnTrue
if object is an instance of any of the types. If classinfo is not a type or tuple of types and such tuples, aTypeError
exception is raised.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 a Union Type, in which case returnTrue
if class is a subclass of any entry in classinfo. In any other case, aTypeError
exception is raised.Changed in version 3.10: classinfo can be a Union Type.
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 at0
). 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
raisesOverflowError
on lengths larger thansys.maxsize
, such asrange(2 ** 100)
.
- 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()
andglobals()
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, …)Return an iterator that applies function to every item of iterable, yielding the results. If additional iterable arguments are passed, function must take that many arguments and is applied to the items from all iterables in parallel. With multiple iterables, the iterator stops when the shortest iterable is exhausted. For cases where the function inputs are already arranged into argument tuples, see
itertools.starmap()
.
max
(iterable, *[, 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, aValueError
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]
andheapq.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, 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, aValueError
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]
andheapq.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])Retrieve the next item from the iterator by calling its
__next__()
method. If default is given, it is returned if the iterator is exhausted, otherwiseStopIteration
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.
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.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
'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 asbytes
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 asstr
, 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 behavior 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. Note that specifying a buffer size this way applies for binary buffered I/O, but
TextIOWrapper
(i.e., files opened withmode='r+'
) would have another buffering. To disable buffering inTextIOWrapper
, consider using thewrite_through
flag forio.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()
returnsTrue
) 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 thecodecs
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 aValueError
exception if there is an encoding error. The default value ofNone
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 thesurrogateescape
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.
'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 beTrue
(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 passingNone
).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. Whenopen()
is used to open a file in a text mode ('w'
,'r'
,'wt'
,'rt'
, etc.), it returns a subclass ofio.TextIOBase
(specificallyio.TextIOWrapper
). When used to open a file in a binary mode with buffering, the returned class is a subclass ofio.BufferedIOBase
. The exact class varies: in read binary mode, it returns anio.BufferedReader
; in write binary and append binary modes, it returns anio.BufferedWriter
, and in read/write mode, it returns anio.BufferedRandom
. When buffering is disabled, the raw stream, a subclass ofio.RawIOBase
,io.FileIO
, is returned.See also the file handling modules, such as
fileinput
,io
(whereopen()
is declared),os
,os.path
,tempfile
, andshutil
.Raises an auditing event
open
with argumentsfile
,mode
,flags
.The
mode
andflags
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.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.
Deprecated since version 3.4, removed in version 3.10: 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
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 thanio.FileIO
.
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 integer97
andord('€')
(Euro sign) returns8364
. This is the inverse ofchr()
.
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 formpow(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)
returns100
, butpow(10, -2)
returns0.01
. For a negative base of typeint
orfloat
and a non-integral exponent, a complex result is delivered. For example,pow(-9, 0.5)
returns a value close to3j
.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
modulo97
:>>>
>>> pow(38, -1, mod=97) 23 >>> 23 * 38 % 97 == 1 True
Changed in version 3.8: For
int
operands, the three-argument form ofpow
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 beNone
, 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 orNone
,sys.stdout
will be used. Since printed arguments are converted to text strings,print()
cannot be used with binary mode file objects. For these, usefile.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, anddel 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 thevoltage()
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
, anddeleter
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
, andfdel
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]) 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.
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 at0
).
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, bothround(0.5)
andround(-0.5)
are0
, andround(1.5)
is2
). Any integer value is valid for ndigits (positive, zero, or negative). The return value is an integer if ndigits is omitted orNone
. Otherwise, the return value has the same type as number.For a general Python object
number
,round
delegates tonumber.__round__
.Note
The behavior of
round()
for floats can be surprising: for example,round(2.675, 2)
gives2.67
instead of the expected2.68
. 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
([iterable]) Return a new
set
object, optionally with elements taken from iterable.set
is a built-in class. Seeset
and Set Types — set, frozenset for documentation about this class.For other containers see the built-in
frozenset
,list
,tuple
, anddict
classes, as well as thecollections
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 tox.foobar = 123
.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]) Return a slice object representing the set of indices specified by
range(start, stop, step)
. The start and step arguments default toNone
. Slice objects have read-only data attributesstart
,stop
, andstep
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]
ora[start:stop, i]
. Seeitertools.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 isNone
(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 asmax()
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 asC().f()
). Moreover, they can be called as regular functions (such asf()
).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. Seestr()
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, seemath.fsum()
. To concatenate a series of iterables, consider usingitertools.chain()
.Changed in version 3.8: The start parameter can be specified as a keyword argument.
- class
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 isD -> B -> C -> A -> object
and the value of type isB
, thensuper()
searchesC -> A -> object
.The
__mro__
attribute of the object-or-type lists the method resolution search order used by bothgetattr()
andsuper()
. 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 assuper().__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 assuper()[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
([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 identicaltype
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 overridetype.__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 atypes.MappingProxyType
to prevent direct dictionary updates).Without an argument,
vars()
acts likelocals()
. 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 afor
loop or by wrapping in alist
.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 thestrict=True
option. Its output is the same as regularzip()
:>>>
>>> list(zip(('a', 'b', 'c'), (1, 2, 3), strict=True)) [('a', 1), ('b', 2), ('c', 3)]
Unlike the default behavior, it checks that the lengths of iterables are identical, raising a
ValueError
if they aren’t:>>>
>>> list(zip(range(3), ['fee', 'fi', 'fo', 'fum'], strict=True)) 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 iteratorn
times so that each output tuple has the result ofn
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 thebuiltins
module and assigning tobuiltins.__import__
) in order to change semantics of theimport
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 ofimportlib.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 theimport
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 variablePYTHONCASEOK
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.
Built-in Constants
A small number of constants live in the built-in namespace. They are:
False
The false value of the
bool
type. Assignments toFalse
are illegal and raise aSyntaxError
.
True
The true value of the
bool
type. Assignments toTrue
are illegal and raise aSyntaxError
.
None
An object frequently used to represent the absence of a value, as when default arguments are not passed to a function. Assignments to
None
are illegal and raise aSyntaxError
.None
is the sole instance of theNoneType
type.
NotImplemented
A special value which should be returned by the binary special methods (e.g.
__eq__()
,__lt__()
,__add__()
,__rsub__()
, etc.) to indicate that the operation is not implemented with respect to the other type; may be returned by the in-place binary special methods (e.g.__imul__()
,__iand__()
, etc.) for the same purpose. It should not be evaluated in a boolean context.NotImplemented
is the sole instance of thetypes.NotImplementedType
type.Note
When a binary (or in-place) method returns
NotImplemented
the interpreter will try the reflected operation on the other type (or some other fallback, depending on the operator). If all attempts returnNotImplemented
, the interpreter will raise an appropriate exception. Incorrectly returningNotImplemented
will result in a misleading error message or theNotImplemented
value being returned to Python code.See Implementing the arithmetic operations for examples.
Note
NotImplementedError
andNotImplemented
are not interchangeable, even though they have similar names and purposes. SeeNotImplementedError
for details on when to use it.Changed in version 3.9: Evaluating
NotImplemented
in a boolean context is deprecated. While it currently evaluates as true, it will emit aDeprecationWarning
. It will raise aTypeError
in a future version of Python.
Ellipsis
The same as the ellipsis literal “
...
”. Special value used mostly in conjunction with extended slicing syntax for user-defined container data types.Ellipsis
is the sole instance of thetypes.EllipsisType
type.
__debug__
This constant is true if Python was not started with an
-O
option. See also theassert
statement.
Note
The names None
, False
, True
and __debug__
cannot be reassigned (assignments to them, even as an attribute name, raise SyntaxError
), so they can be considered “true” constants.
Constants added by the site
module
The site
module (which is imported automatically during startup, except if the -S
command-line option is given) adds several constants to the built-in namespace. They are useful for the interactive interpreter shell and should not be used in programs.
quit
(code=None)exit
(code=None)Objects that when printed, print a message like “Use quit() or Ctrl-D (i.e. EOF) to exit”, and when called, raise
SystemExit
with the specified exit code.
copyright
credits
Objects that when printed or called, print the text of copyright or credits, respectively.
license
Object that when printed, prints the message “Type license() to see the full license text”, and when called, displays the full license text in a pager-like fashion (one screen at a time).
Built-in Types
The following sections describe the standard types that are built into the interpreter.
The principal built-in types are numerics, sequences, mappings, classes, instances and exceptions.
Some collection classes are mutable. The methods that add, subtract, or rearrange their members in place, and don’t return a specific item, never return the collection instance itself but None
.
Some operations are supported by several object types; in particular, practically all objects can be compared for equality, tested for truth value, and converted to a string (with the repr()
function or the slightly different str()
function). The latter function is implicitly used when an object is written by the print()
function.
Truth Value Testing
Any object can be tested for truth value, for use in an if
or while
condition or as operand of the Boolean operations below.
By default, an object is considered true unless its class defines either a __bool__()
method that returns False
or a __len__()
method that returns zero, when called with the object. 1 Here are most of the built-in objects considered false:
constants defined to be false:
None
andFalse
.zero of any numeric type:
0
,0.0
,0j
,Decimal(0)
,Fraction(0, 1)
empty sequences and collections:
''
,()
,[]
,{}
,set()
,range(0)
Operations and built-in functions that have a Boolean result always return 0
or False
for false and 1
or True
for true, unless otherwise stated. (Important exception: the Boolean operations or
and and
always return one of their operands.)
Boolean Operations — and
, or
, not
These are the Boolean operations, ordered by ascending priority:
Operation | Result | Notes |
---|---|---|
| if x is false, then y, else x | (1) |
| if x is false, then x, else y | (2) |
| if x is false, then | (3) |
Notes:
This is a short-circuit operator, so it only evaluates the second argument if the first one is false.
This is a short-circuit operator, so it only evaluates the second argument if the first one is true.
not
has a lower priority than non-Boolean operators, sonot a == b
is interpreted asnot (a == b)
, anda == not b
is a syntax error.
Comparisons
There are eight comparison operations in Python. They all have the same priority (which is higher than that of the Boolean operations). Comparisons can be chained arbitrarily; for example, x < y <= z
is equivalent to x < y and y <= z
, except that y is evaluated only once (but in both cases z is not evaluated at all when x < y
is found to be false).
This table summarizes the comparison operations:
Operation | Meaning |
---|---|
| strictly less than |
| less than or equal |
| strictly greater than |
| greater than or equal |
| equal |
| not equal |
| object identity |
| negated object identity |
Objects of different types, except different numeric types, never compare equal. The ==
operator is always defined but for some object types (for example, class objects) is equivalent to is
. The <
, <=
, >
and >=
operators are only defined where they make sense; for example, they raise a TypeError
exception when one of the arguments is a complex number.
Non-identical instances of a class normally compare as non-equal unless the class defines the __eq__()
method.
Instances of a class cannot be ordered with respect to other instances of the same class, or other types of object, unless the class defines enough of the methods __lt__()
, __le__()
, __gt__()
, and __ge__()
(in general, __lt__()
and __eq__()
are sufficient, if you want the conventional meanings of the comparison operators).
The behavior of the is
and is not
operators cannot be customized; also they can be applied to any two objects and never raise an exception.
Two more operations with the same syntactic priority, in
and not in
, are supported by types that are iterable or implement the __contains__()
method.
Numeric Types — int
, float
, complex
There are three distinct numeric types: integers, floating point numbers, and complex numbers. In addition, Booleans are a subtype of integers. Integers have unlimited precision. Floating point numbers are usually implemented using double in C; information about the precision and internal representation of floating point numbers for the machine on which your program is running is available in sys.float_info
. Complex numbers have a real and imaginary part, which are each a floating point number. To extract these parts from a complex number z, use z.real
and z.imag
. (The standard library includes the additional numeric types fractions.Fraction
, for rationals, and decimal.Decimal
, for floating-point numbers with user-definable precision.)
Numbers are created by numeric literals or as the result of built-in functions and operators. Unadorned integer literals (including hex, octal and binary numbers) yield integers. Numeric literals containing a decimal point or an exponent sign yield floating point numbers. Appending 'j'
or 'J'
to a numeric literal yields an imaginary number (a complex number with a zero real part) which you can add to an integer or float to get a complex number with real and imaginary parts.
Python fully supports mixed arithmetic: when a binary arithmetic operator has operands of different numeric types, the operand with the “narrower” type is widened to that of the other, where integer is narrower than floating point, which is narrower than complex. A comparison between numbers of different types behaves as though the exact values of those numbers were being compared. 2
The constructors int()
, float()
, and complex()
can be used to produce numbers of a specific type.
All numeric types (except complex) support the following operations (for priorities of the operations, see Operator precedence):
Operation | Result | Notes | Full documentation |
---|---|---|---|
| sum of x and y | ||
| difference of x and y | ||
| product of x and y | ||
| quotient of x and y | ||
| floored quotient of x and y | (1) | |
| remainder of | (2) | |
| x negated | ||
| x unchanged | ||
| absolute value or magnitude of x | ||
| x converted to integer | (3)(6) | |
| x converted to floating point | (4)(6) | |
| a complex number with real part re, imaginary part im. im defaults to zero. | (6) | |
| conjugate of the complex number c | ||
| the pair | (2) | |
| x to the power y | (5) | |
| x to the power y | (5) |
Notes:
Also referred to as integer division. The resultant value is a whole integer, though the result’s type is not necessarily int. The result is always rounded towards minus infinity:
1//2
is0
,(-1)//2
is-1
,1//(-2)
is-1
, and(-1)//(-2)
is0
.Not for complex numbers. Instead convert to floats using
abs()
if appropriate.Conversion from floating point to integer may round or truncate as in C; see functions
math.floor()
andmath.ceil()
for well-defined conversions.float also accepts the strings “nan” and “inf” with an optional prefix “+” or “-” for Not a Number (NaN) and positive or negative infinity.
Python defines
pow(0, 0)
and0 ** 0
to be1
, as is common for programming languages.The numeric literals accepted include the digits
0
to9
or any Unicode equivalent (code points with theNd
property).See https://www.unicode.org/Public/13.0.0/ucd/extracted/DerivedNumericType.txt for a complete list of code points with the
Nd
property.
All numbers.Real
types (int
and float
) also include the following operations:
Operation | Result |
---|---|
x truncated to | |
x rounded to n digits, rounding half to even. If n is omitted, it defaults to 0. | |
the greatest | |
the least |
For additional numeric operations see the math
and cmath
modules.
Bitwise Operations on Integer Types
Bitwise operations only make sense for integers. The result of bitwise operations is calculated as though carried out in two’s complement with an infinite number of sign bits.
The priorities of the binary bitwise operations are all lower than the numeric operations and higher than the comparisons; the unary operation ~
has the same priority as the other unary numeric operations (+
and -
).
This table lists the bitwise operations sorted in ascending priority:
Operation | Result | Notes |
---|---|---|
| bitwise or of x and y | (4) |
| bitwise exclusive or of x and y | (4) |
| bitwise and of x and y | (4) |
| x shifted left by n bits | (1)(2) |
| x shifted right by n bits | (1)(3) |
| the bits of x inverted |
Notes:
Negative shift counts are illegal and cause a
ValueError
to be raised.A left shift by n bits is equivalent to multiplication by
pow(2, n)
.A right shift by n bits is equivalent to floor division by
pow(2, n)
.Performing these calculations with at least one extra sign extension bit in a finite two’s complement representation (a working bit-width of
1 + max(x.bit_length(), y.bit_length())
or more) is sufficient to get the same result as if there were an infinite number of sign bits.
Additional Methods on Integer Types
The int type implements the numbers.Integral
abstract base class. In addition, it provides a few more methods:
int.
bit_length
()Return the number of bits necessary to represent an integer in binary, excluding the sign and leading zeros:
>>>
>>> n = -37 >>> bin(n) '-0b100101' >>> n.bit_length() 6
More precisely, if
x
is nonzero, thenx.bit_length()
is the unique positive integerk
such that2**(k-1) <= abs(x) < 2**k
. Equivalently, whenabs(x)
is small enough to have a correctly rounded logarithm, thenk = 1 + int(log(abs(x), 2))
. Ifx
is zero, thenx.bit_length()
returns0
.Equivalent to:
def bit_length(self): s = bin(self) # binary representation: bin(-37) --> '-0b100101' s = s.lstrip('-0b') # remove leading zeros and minus sign return len(s) # len('100101') --> 6
New in version 3.1.
int.
bit_count
()Return the number of ones in the binary representation of the absolute value of the integer. This is also known as the population count. Example:
>>>
>>> n = 19 >>> bin(n) '0b10011' >>> n.bit_count() 3 >>> (-n).bit_count() 3
Equivalent to:
def bit_count(self): return bin(self).count("1")
New in version 3.10.
int.
to_bytes
(length, byteorder, *, signed=False)Return an array of bytes representing an integer.
>>>
>>> (1024).to_bytes(2, byteorder='big') b'\x04\x00' >>> (1024).to_bytes(10, byteorder='big') b'\x00\x00\x00\x00\x00\x00\x00\x00\x04\x00' >>> (-1024).to_bytes(10, byteorder='big', signed=True) b'\xff\xff\xff\xff\xff\xff\xff\xff\xfc\x00' >>> x = 1000 >>> x.to_bytes((x.bit_length() + 7) // 8, byteorder='little') b'\xe8\x03'
The integer is represented using length bytes. An
OverflowError
is raised if the integer is not representable with the given number of bytes.The byteorder argument determines the byte order used to represent the integer. If byteorder is
"big"
, the most significant byte is at the beginning of the byte array. If byteorder is"little"
, the most significant byte is at the end of the byte array. To request the native byte order of the host system, usesys.byteorder
as the byte order value.The signed argument determines whether two’s complement is used to represent the integer. If signed is
False
and a negative integer is given, anOverflowError
is raised. The default value for signed isFalse
.New in version 3.2.
- classmethod
int.
from_bytes
(bytes, byteorder, *, signed=False) Return the integer represented by the given array of bytes.
>>>
>>> int.from_bytes(b'\x00\x10', byteorder='big') 16 >>> int.from_bytes(b'\x00\x10', byteorder='little') 4096 >>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=True) -1024 >>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=False) 64512 >>> int.from_bytes([255, 0, 0], byteorder='big') 16711680
The argument bytes must either be a bytes-like object or an iterable producing bytes.
The byteorder argument determines the byte order used to represent the integer. If byteorder is
"big"
, the most significant byte is at the beginning of the byte array. If byteorder is"little"
, the most significant byte is at the end of the byte array. To request the native byte order of the host system, usesys.byteorder
as the byte order value.The signed argument indicates whether two’s complement is used to represent the integer.
New in version 3.2.
int.
as_integer_ratio
()Return a pair of integers whose ratio is exactly equal to the original integer and with a positive denominator. The integer ratio of integers (whole numbers) is always the integer as the numerator and
1
as the denominator.New in version 3.8.
Additional Methods on Float
The float type implements the numbers.Real
abstract base class. float also has the following additional methods.
float.
as_integer_ratio
()Return a pair of integers whose ratio is exactly equal to the original float and with a positive denominator. Raises
OverflowError
on infinities and aValueError
on NaNs.
float.
is_integer
()Return
True
if the float instance is finite with integral value, andFalse
otherwise:>>>
>>> (-2.0).is_integer() True >>> (3.2).is_integer() False
Two methods support conversion to and from hexadecimal strings. Since Python’s floats are stored internally as binary numbers, converting a float to or from a decimal string usually involves a small rounding error. In contrast, hexadecimal strings allow exact representation and specification of floating-point numbers. This can be useful when debugging, and in numerical work.
float.
hex
()Return a representation of a floating-point number as a hexadecimal string. For finite floating-point numbers, this representation will always include a leading
0x
and a trailingp
and exponent.
- classmethod
float.
fromhex
(s) Class method to return the float represented by a hexadecimal string s. The string s may have leading and trailing whitespace.
Note that float.hex()
is an instance method, while float.fromhex()
is a class method.
A hexadecimal string takes the form:
[sign] ['0x'] integer ['.' fraction] ['p' exponent]
where the optional sign
may by either +
or -
, integer
and fraction
are strings of hexadecimal digits, and exponent
is a decimal integer with an optional leading sign. Case is not significant, and there must be at least one hexadecimal digit in either the integer or the fraction. This syntax is similar to the syntax specified in section 6.4.4.2 of the C99 standard, and also to the syntax used in Java 1.5 onwards. In particular, the output of float.hex()
is usable as a hexadecimal floating-point literal in C or Java code, and hexadecimal strings produced by C’s %a
format character or Java’s Double.toHexString
are accepted by float.fromhex()
.
Note that the exponent is written in decimal rather than hexadecimal, and that it gives the power of 2 by which to multiply the coefficient. For example, the hexadecimal string 0x3.a7p10
represents the floating-point number (3 + 10./16 + 7./16**2) * 2.0**10
, or 3740.0
:
>>>
>>> float.fromhex('0x3.a7p10')
3740.0
Applying the reverse conversion to 3740.0
gives a different hexadecimal string representing the same number:
>>>
>>> float.hex(3740.0)
'0x1.d380000000000p+11'
Hashing of numeric types
For numbers x
and y
, possibly of different types, it’s a requirement that hash(x) == hash(y)
whenever x == y
(see the __hash__()
method documentation for more details). For ease of implementation and efficiency across a variety of numeric types (including int
, float
, decimal.Decimal
and fractions.Fraction
) Python’s hash for numeric types is based on a single mathematical function that’s defined for any rational number, and hence applies to all instances of int
and fractions.Fraction
, and all finite instances of float
and decimal.Decimal
. Essentially, this function is given by reduction modulo P
for a fixed prime P
. The value of P
is made available to Python as the modulus
attribute of sys.hash_info
.
CPython implementation detail: Currently, the prime used is P = 2**31 - 1
on machines with 32-bit C longs and P = 2**61 - 1
on machines with 64-bit C longs.
Here are the rules in detail:
If
x = m / n
is a nonnegative rational number andn
is not divisible byP
, definehash(x)
asm * invmod(n, P) % P
, whereinvmod(n, P)
gives the inverse ofn
moduloP
.If
x = m / n
is a nonnegative rational number andn
is divisible byP
(butm
is not) thenn
has no inverse moduloP
and the rule above doesn’t apply; in this case definehash(x)
to be the constant valuesys.hash_info.inf
.If
x = m / n
is a negative rational number definehash(x)
as-hash(-x)
. If the resulting hash is-1
, replace it with-2
.The particular values
sys.hash_info.inf
and-sys.hash_info.inf
are used as hash values for positive infinity or negative infinity (respectively).For a
complex
numberz
, the hash values of the real and imaginary parts are combined by computinghash(z.real) + sys.hash_info.imag * hash(z.imag)
, reduced modulo2**sys.hash_info.width
so that it lies inrange(-2**(sys.hash_info.width - 1), 2**(sys.hash_info.width - 1))
. Again, if the result is-1
, it’s replaced with-2
.
To clarify the above rules, here’s some example Python code, equivalent to the built-in hash, for computing the hash of a rational number, float
, or complex
:
import sys, math
def hash_fraction(m, n):
"""Compute the hash of a rational number m / n.
Assumes m and n are integers, with n positive.
Equivalent to hash(fractions.Fraction(m, n)).
"""
P = sys.hash_info.modulus
# Remove common factors of P. (Unnecessary if m and n already coprime.)
while m % P == n % P == 0:
m, n = m // P, n // P
if n % P == 0:
hash_value = sys.hash_info.inf
else:
# Fermat's Little Theorem: pow(n, P-1, P) is 1, so
# pow(n, P-2, P) gives the inverse of n modulo P.
hash_value = (abs(m) % P) * pow(n, P - 2, P) % P
if m < 0:
hash_value = -hash_value
if hash_value == -1:
hash_value = -2
return hash_value
def hash_float(x):
"""Compute the hash of a float x."""
if math.isnan(x):
return object.__hash__(x)
elif math.isinf(x):
return sys.hash_info.inf if x > 0 else -sys.hash_info.inf
else:
return hash_fraction(*x.as_integer_ratio())
def hash_complex(z):
"""Compute the hash of a complex number z."""
hash_value = hash_float(z.real) + sys.hash_info.imag * hash_float(z.imag)
# do a signed reduction modulo 2**sys.hash_info.width
M = 2**(sys.hash_info.width - 1)
hash_value = (hash_value & (M - 1)) - (hash_value & M)
if hash_value == -1:
hash_value = -2
return hash_value
Iterator Types
Python supports a concept of iteration over containers. This is implemented using two distinct methods; these are used to allow user-defined classes to support iteration. Sequences, described below in more detail, always support the iteration methods.
One method needs to be defined for container objects to provide iterable support:
container.
__iter__
()Return an iterator object. The object is required to support the iterator protocol described below. If a container supports different types of iteration, additional methods can be provided to specifically request iterators for those iteration types. (An example of an object supporting multiple forms of iteration would be a tree structure which supports both breadth-first and depth-first traversal.) This method corresponds to the
tp_iter
slot of the type structure for Python objects in the Python/C API.
The iterator objects themselves are required to support the following two methods, which together form the iterator protocol:
iterator.
__iter__
()Return the iterator object itself. This is required to allow both containers and iterators to be used with the
for
andin
statements. This method corresponds to thetp_iter
slot of the type structure for Python objects in the Python/C API.
iterator.
__next__
()Return the next item from the iterator. If there are no further items, raise the
StopIteration
exception. This method corresponds to thetp_iternext
slot of the type structure for Python objects in the Python/C API.
Python defines several iterator objects to support iteration over general and specific sequence types, dictionaries, and other more specialized forms. The specific types are not important beyond their implementation of the iterator protocol.
Once an iterator’s __next__()
method raises StopIteration
, it must continue to do so on subsequent calls. Implementations that do not obey this property are deemed broken.
Generator Types
Python’s generators provide a convenient way to implement the iterator protocol. If a container object’s __iter__()
method is implemented as a generator, it will automatically return an iterator object (technically, a generator object) supplying the __iter__()
and __next__()
methods. More information about generators can be found in the documentation for the yield expression.
Sequence Types — list
, tuple
, range
There are three basic sequence types: lists, tuples, and range objects. Additional sequence types tailored for processing of binary data and text strings are described in dedicated sections.
Common Sequence Operations
The operations in the following table are supported by most sequence types, both mutable and immutable. The collections.abc.Sequence
ABC is provided to make it easier to correctly implement these operations on custom sequence types.
This table lists the sequence operations sorted in ascending priority. In the table, s and t are sequences of the same type, n, i, j and k are integers and x is an arbitrary object that meets any type and value restrictions imposed by s.
The in
and not in
operations have the same priorities as the comparison operations. The +
(concatenation) and *
(repetition) operations have the same priority as the corresponding numeric operations. 3
Operation | Result | Notes |
---|---|---|
|
| (1) |
|
| (1) |
| the concatenation of s and t | (6)(7) |
| equivalent to adding s to itself n times | (2)(7) |
| ith item of s, origin 0 | (3) |
| slice of s from i to j | (3)(4) |
| slice of s from i to j with step k | (3)(5) |
| length of s | |
| smallest item of s | |
| largest item of s | |
| index of the first occurrence of x in s (at or after index i and before index j) | (8) |
| total number of occurrences of x in s |
Sequences of the same type also support comparisons. In particular, tuples and lists are compared lexicographically by comparing corresponding elements. This means that to compare equal, every element must compare equal and the two sequences must be of the same type and have the same length. (For full details see Comparisons in the language reference.)
Forward and reversed iterators over mutable sequences access values using an index. That index will continue to march forward (or backward) even if the underlying sequence is mutated. The iterator terminates only when an IndexError
or a StopIteration
is encountered (or when the index drops below zero).
Notes:
While the
in
andnot in
operations are used only for simple containment testing in the general case, some specialised sequences (such asstr
,bytes
andbytearray
) also use them for subsequence testing:>>>
>>> "gg" in "eggs" True
Values of n less than
0
are treated as0
(which yields an empty sequence of the same type as s). Note that items in the sequence s are not copied; they are referenced multiple times. This often haunts new Python programmers; consider:>>>
>>> lists = [[]] * 3 >>> lists [[], [], []] >>> lists[0].append(3) >>> lists [[3], [3], [3]]
What has happened is that
[[]]
is a one-element list containing an empty list, so all three elements of[[]] * 3
are references to this single empty list. Modifying any of the elements oflists
modifies this single list. You can create a list of different lists this way:>>>
>>> lists = [[] for i in range(3)] >>> lists[0].append(3) >>> lists[1].append(5) >>> lists[2].append(7) >>> lists [[3], [5], [7]]
Further explanation is available in the FAQ entry How do I create a multidimensional list?.
If i or j is negative, the index is relative to the end of sequence s:
len(s) + i
orlen(s) + j
is substituted. But note that-0
is still0
.The slice of s from i to j is defined as the sequence of items with index k such that
i <= k < j
. If i or j is greater thanlen(s)
, uselen(s)
. If i is omitted orNone
, use0
. If j is omitted orNone
, uselen(s)
. If i is greater than or equal to j, the slice is empty.The slice of s from i to j with step k is defined as the sequence of items with index
x = i + n*k
such that0 <= n < (j-i)/k
. In other words, the indices arei
,i+k
,i+2*k
,i+3*k
and so on, stopping when j is reached (but never including j). When k is positive, i and j are reduced tolen(s)
if they are greater. When k is negative, i and j are reduced tolen(s) - 1
if they are greater. If i or j are omitted orNone
, they become “end” values (which end depends on the sign of k). Note, k cannot be zero. If k isNone
, it is treated like1
.Concatenating immutable sequences always results in a new object. This means that building up a sequence by repeated concatenation will have a quadratic runtime cost in the total sequence length. To get a linear runtime cost, you must switch to one of the alternatives below:
if concatenating
str
objects, you can build a list and usestr.join()
at the end or else write to anio.StringIO
instance and retrieve its value when completeif concatenating
bytes
objects, you can similarly usebytes.join()
orio.BytesIO
, or you can do in-place concatenation with abytearray
object.bytearray
objects are mutable and have an efficient overallocation mechanismfor other types, investigate the relevant class documentation
Some sequence types (such as
range
) only support item sequences that follow specific patterns, and hence don’t support sequence concatenation or repetition.index
raisesValueError
when x is not found in s. Not all implementations support passing the additional arguments i and j. These arguments allow efficient searching of subsections of the sequence. Passing the extra arguments is roughly equivalent to usings[i:j].index(x)
, only without copying any data and with the returned index being relative to the start of the sequence rather than the start of the slice.
Immutable Sequence Types
The only operation that immutable sequence types generally implement that is not also implemented by mutable sequence types is support for the hash()
built-in.
This support allows immutable sequences, such as tuple
instances, to be used as dict
keys and stored in set
and frozenset
instances.
Attempting to hash an immutable sequence that contains unhashable values will result in TypeError
.
Mutable Sequence Types
The operations in the following table are defined on mutable sequence types. The collections.abc.MutableSequence
ABC is provided to make it easier to correctly implement these operations on custom sequence types.
In the table s is an instance of a mutable sequence type, t is any iterable object and x is an arbitrary object that meets any type and value restrictions imposed by s (for example, bytearray
only accepts integers that meet the value restriction 0 <= x <= 255
).
Operation | Result | Notes |
---|---|---|
| item i of s is replaced by x | |
| slice of s from i to j is replaced by the contents of the iterable t | |
| same as | |
| the elements of | (1) |
| removes the elements of | |
| appends x to the end of the sequence (same as | |
| removes all items from s (same as | (5) |
| creates a shallow copy of s (same as | (5) |
| extends s with the contents of t (for the most part the same as | |
| updates s with its contents repeated n times | (6) |
| inserts x into s at the index given by i (same as | |
| retrieves the item at i and also removes it from s | (2) |
| remove the first item from s where | (3) |
| reverses the items of s in place | (4) |
Notes:
t must have the same length as the slice it is replacing.
The optional argument i defaults to
-1
, so that by default the last item is removed and returned.remove()
raisesValueError
when x is not found in s.The
reverse()
method modifies the sequence in place for economy of space when reversing a large sequence. To remind users that it operates by side effect, it does not return the reversed sequence.clear()
andcopy()
are included for consistency with the interfaces of mutable containers that don’t support slicing operations (such asdict
andset
).copy()
is not part of thecollections.abc.MutableSequence
ABC, but most concrete mutable sequence classes provide it.New in version 3.3:
clear()
andcopy()
methods.The value n is an integer, or an object implementing
__index__()
. Zero and negative values of n clear the sequence. Items in the sequence are not copied; they are referenced multiple times, as explained fors * n
under Common Sequence Operations.
Lists
Lists are mutable sequences, typically used to store collections of homogeneous items (where the precise degree of similarity will vary by application).
- class
list
([iterable]) Lists may be constructed in several ways:
Using a pair of square brackets to denote the empty list:
[]
Using square brackets, separating items with commas:
[a]
,[a, b, c]
Using a list comprehension:
[x for x in iterable]
Using the type constructor:
list()
orlist(iterable)
The constructor builds a list whose items are the same and in the same order as iterable’s items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a list, a copy is made and returned, similar to
iterable[:]
. For example,list('abc')
returns['a', 'b', 'c']
andlist( (1, 2, 3) )
returns[1, 2, 3]
. If no argument is given, the constructor creates a new empty list,[]
.Many other operations also produce lists, including the
sorted()
built-in.Lists implement all of the common and mutable sequence operations. Lists also provide the following additional method:
sort
(*, key=None, reverse=False)This method sorts the list in place, using only
<
comparisons between items. Exceptions are not suppressed – if any comparison operations fail, the entire sort operation will fail (and the list will likely be left in a partially modified state).sort()
accepts two arguments that can only be passed by keyword (keyword-only arguments):key specifies a function of one argument that is used to extract a comparison key from each list element (for example,
key=str.lower
). The key corresponding to each item in the list is calculated once and then used for the entire sorting process. The default value ofNone
means that list items are sorted directly without calculating a separate key value.The
functools.cmp_to_key()
utility is available to convert a 2.x style cmp function to a key function.reverse is a boolean value. If set to
True
, then the list elements are sorted as if each comparison were reversed.This method modifies the sequence in place for economy of space when sorting a large sequence. To remind users that it operates by side effect, it does not return the sorted sequence (use
sorted()
to explicitly request a new sorted list instance).The
sort()
method 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.
CPython implementation detail: While a list is being sorted, the effect of attempting to mutate, or even inspect, the list is undefined. The C implementation of Python makes the list appear empty for the duration, and raises
ValueError
if it can detect that the list has been mutated during a sort.
Tuples
Tuples are immutable sequences, typically used to store collections of heterogeneous data (such as the 2-tuples produced by the enumerate()
built-in). Tuples are also used for cases where an immutable sequence of homogeneous data is needed (such as allowing storage in a set
or dict
instance).
- class
tuple
([iterable]) Tuples may be constructed in a number of ways:
Using a pair of parentheses to denote the empty tuple:
()
Using a trailing comma for a singleton tuple:
a,
or(a,)
Separating items with commas:
a, b, c
or(a, b, c)
Using the
tuple()
built-in:tuple()
ortuple(iterable)
The constructor builds a tuple whose items are the same and in the same order as iterable’s items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a tuple, it is returned unchanged. For example,
tuple('abc')
returns('a', 'b', 'c')
andtuple( [1, 2, 3] )
returns(1, 2, 3)
. If no argument is given, the constructor creates a new empty tuple,()
.Note that it is actually the comma which makes a tuple, not the parentheses. The parentheses are optional, except in the empty tuple case, or when they are needed to avoid syntactic ambiguity. For example,
f(a, b, c)
is a function call with three arguments, whilef((a, b, c))
is a function call with a 3-tuple as the sole argument.Tuples implement all of the common sequence operations.
For heterogeneous collections of data where access by name is clearer than access by index, collections.namedtuple()
may be a more appropriate choice than a simple tuple object.
Ranges
The range
type represents an immutable sequence of numbers and is commonly used for looping a specific number of times in for
loops.
- class
range
(stop) - class
range
(start, stop[, step]) The arguments to the range constructor must be integers (either built-in
int
or any object that implements the__index__()
special method). If the step argument is omitted, it defaults to1
. If the start argument is omitted, it defaults to0
. If step is zero,ValueError
is raised.For a positive step, the contents of a range
r
are determined by the formular[i] = start + step*i
wherei >= 0
andr[i] < stop
.For a negative step, the contents of the range are still determined by the formula
r[i] = start + step*i
, but the constraints arei >= 0
andr[i] > stop
.A range object will be empty if
r[0]
does not meet the value constraint. Ranges do support negative indices, but these are interpreted as indexing from the end of the sequence determined by the positive indices.Ranges containing absolute values larger than
sys.maxsize
are permitted but some features (such aslen()
) may raiseOverflowError
.Range examples:
>>>
>>> list(range(10)) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> list(range(1, 11)) [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> list(range(0, 30, 5)) [0, 5, 10, 15, 20, 25] >>> list(range(0, 10, 3)) [0, 3, 6, 9] >>> list(range(0, -10, -1)) [0, -1, -2, -3, -4, -5, -6, -7, -8, -9] >>> list(range(0)) [] >>> list(range(1, 0)) []
Ranges implement all of the common sequence operations except concatenation and repetition (due to the fact that range objects can only represent sequences that follow a strict pattern and repetition and concatenation will usually violate that pattern).
start
The value of the start parameter (or
0
if the parameter was not supplied)
stop
The value of the stop parameter
step
The value of the step parameter (or
1
if the parameter was not supplied)
The advantage of the range
type over a regular list
or tuple
is that a range
object will always take the same (small) amount of memory, no matter the size of the range it represents (as it only stores the start
, stop
and step
values, calculating individual items and subranges as needed).
Range objects implement the collections.abc.Sequence
ABC, and provide features such as containment tests, element index lookup, slicing and support for negative indices (see Sequence Types — list, tuple, range):
>>>
>>> r = range(0, 20, 2)
>>> r
range(0, 20, 2)
>>> 11 in r
False
>>> 10 in r
True
>>> r.index(10)
5
>>> r[5]
10
>>> r[:5]
range(0, 10, 2)
>>> r[-1]
18
Testing range objects for equality with ==
and !=
compares them as sequences. That is, two range objects are considered equal if they represent the same sequence of values. (Note that two range objects that compare equal might have different start
, stop
and step
attributes, for example range(0) == range(2, 1, 3)
or range(0, 3, 2) == range(0, 4, 2)
.)
Changed in version 3.2: Implement the Sequence ABC. Support slicing and negative indices. Test int
objects for membership in constant time instead of iterating through all items.
Changed in version 3.3: Define ‘==’ and ‘!=’ to compare range objects based on the sequence of values they define (instead of comparing based on object identity).
See also
The linspace recipe shows how to implement a lazy version of range suitable for floating point applications.
Text Sequence Type — str
Textual data in Python is handled with str
objects, or strings. Strings are immutable sequences of Unicode code points. String literals are written in a variety of ways:
Single quotes:
'allows embedded "double" quotes'
Double quotes:
"allows embedded 'single' quotes"
Triple quoted:
'''Three single quotes'''
,"""Three double quotes"""
Triple quoted strings may span multiple lines – all associated whitespace will be included in the string literal.
String literals that are part of a single expression and have only whitespace between them will be implicitly converted to a single string literal. That is, ("spam " "eggs") == "spam eggs"
.
See String and Bytes literals for more about the various forms of string literal, including supported escape sequences, and the r
(“raw”) prefix that disables most escape sequence processing.
Strings may also be created from other objects using the str
constructor.
Since there is no separate “character” type, indexing a string produces strings of length 1. That is, for a non-empty string s, s[0] == s[0:1]
.
There is also no mutable string type, but str.join()
or io.StringIO
can be used to efficiently construct strings from multiple fragments.
Changed in version 3.3: For backwards compatibility with the Python 2 series, the u
prefix is once again permitted on string literals. It has no effect on the meaning of string literals and cannot be combined with the r
prefix.
- class
str
(object=”) - class
str
(object=b”, encoding=‘utf-8’, errors=‘strict’) Return a string version of object. If object is not provided, returns the empty string. Otherwise, the behavior of
str()
depends on whether encoding or errors is given, as follows.If neither encoding nor errors is given,
str(object)
returnstype(object).__str__(object)
, which is the “informal” or nicely printable string representation of object. For string objects, this is the string itself. If object does not have a__str__()
method, thenstr()
falls back to returningrepr(object)
.If at least one of encoding or errors is given, object should be a bytes-like object (e.g.
bytes
orbytearray
). In this case, if object is abytes
(orbytearray
) object, thenstr(bytes, encoding, errors)
is equivalent tobytes.decode(encoding, errors)
. Otherwise, the bytes object underlying the buffer object is obtained before callingbytes.decode()
. See Binary Sequence Types — bytes, bytearray, memoryview and Buffer Protocol for information on buffer objects.Passing a
bytes
object tostr()
without the encoding or errors arguments falls under the first case of returning the informal string representation (see also the-b
command-line option to Python). For example:>>>
>>> str(b'Zoot!') "b'Zoot!'"
For more information on the
str
class and its methods, see Text Sequence Type — str and the String Methods section below. To output formatted strings, see the Formatted string literals and Format String Syntax sections. In addition, see the Text Processing Services section.
String Methods
Strings implement all of the common sequence operations, along with the additional methods described below.
Strings also support two styles of string formatting, one providing a large degree of flexibility and customization (see str.format()
, Format String Syntax and Custom String Formatting) and the other based on C printf
style formatting that handles a narrower range of types and is slightly harder to use correctly, but is often faster for the cases it can handle (printf-style String Formatting).
The Text Processing Services section of the standard library covers a number of other modules that provide various text related utilities (including regular expression support in the re
module).
str.
capitalize
()Return a copy of the string with its first character capitalized and the rest lowercased.
Changed in version 3.8: The first character is now put into titlecase rather than uppercase. This means that characters like digraphs will only have their first letter capitalized, instead of the full character.
str.
casefold
()Return a casefolded copy of the string. Casefolded strings may be used for caseless matching.
Casefolding is similar to lowercasing but more aggressive because it is intended to remove all case distinctions in a string. For example, the German lowercase letter
'ß'
is equivalent to"ss"
. Since it is already lowercase,lower()
would do nothing to'ß'
;casefold()
converts it to"ss"
.The casefolding algorithm is described in section 3.13 of the Unicode Standard.
New in version 3.3.
str.
center
(width[, fillchar])Return centered in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to
len(s)
.
str.
count
(sub[, start[, end]])Return the number of non-overlapping occurrences of substring sub in the range [start, end]. Optional arguments start and end are interpreted as in slice notation.
str.
encode
(encoding=‘utf-8’, errors=‘strict’)Return an encoded version of the string as a bytes object. Default encoding is
'utf-8'
. errors may be given to set a different error handling scheme. The default for errors is'strict'
, meaning that encoding errors raise aUnicodeError
. Other possible values are'ignore'
,'replace'
,'xmlcharrefreplace'
,'backslashreplace'
and any other name registered viacodecs.register_error()
, see section Error Handlers. For a list of possible encodings, see section Standard Encodings.By default, the errors argument is not checked for best performances, but only used at the first encoding error. Enable the Python Development Mode, or use a debug build to check errors.
Changed in version 3.1: Support for keyword arguments added.
Changed in version 3.9: The errors is now checked in development mode and in debug mode.
str.
endswith
(suffix[, start[, end]])Return
True
if the string ends with the specified suffix, otherwise returnFalse
. suffix can also be a tuple of suffixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.
str.
expandtabs
(tabsize=8)Return a copy of the string where all tab characters are replaced by one or more spaces, depending on the current column and the given tab size. Tab positions occur every tabsize characters (default is 8, giving tab positions at columns 0, 8, 16 and so on). To expand the string, the current column is set to zero and the string is examined character by character. If the character is a tab (
\t
), one or more space characters are inserted in the result until the current column is equal to the next tab position. (The tab character itself is not copied.) If the character is a newline (\n
) or return (\r
), it is copied and the current column is reset to zero. Any other character is copied unchanged and the current column is incremented by one regardless of how the character is represented when printed.>>>
>>> '01\t012\t0123\t01234'.expandtabs() '01 012 0123 01234' >>> '01\t012\t0123\t01234'.expandtabs(4) '01 012 0123 01234'
str.
find
(sub[, start[, end]])Return the lowest index in the string where substring sub is found within the slice
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
if sub is not found.
str.
format
(*args, **kwargs)Perform a string formatting operation. The string on which this method is called can contain literal text or replacement fields delimited by braces
{}
. Each replacement field contains either the numeric index of a positional argument, or the name of a keyword argument. Returns a copy of the string where each replacement field is replaced with the string value of the corresponding argument.>>>
>>> "The sum of 1 + 2 is {0}".format(1+2) 'The sum of 1 + 2 is 3'
See Format String Syntax for a description of the various formatting options that can be specified in format strings.
Note
When formatting a number (
int
,float
,complex
,decimal.Decimal
and subclasses) with then
type (ex:'{:n}'.format(1234)
), the function temporarily sets theLC_CTYPE
locale to theLC_NUMERIC
locale to decodedecimal_point
andthousands_sep
fields oflocaleconv()
if they are non-ASCII or longer than 1 byte, and theLC_NUMERIC
locale is different than theLC_CTYPE
locale. This temporary change affects other threads.Changed in version 3.7: When formatting a number with the
n
type, the function sets temporarily theLC_CTYPE
locale to theLC_NUMERIC
locale in some cases.
str.
format_map
(mapping)Similar to
str.format(**mapping)
, except thatmapping
is used directly and not copied to adict
. This is useful if for examplemapping
is a dict subclass:>>>
>>> class Default(dict): ... def __missing__(self, key): ... return key ... >>> '{name} was born in {country}'.format_map(Default(name='Guido')) 'Guido was born in country'
New in version 3.2.
str.
index
(sub[, start[, end]])Like
find()
, but raiseValueError
when the substring is not found.
str.
isalnum
()Return
True
if all characters in the string are alphanumeric and there is at least one character,False
otherwise. A characterc
is alphanumeric if one of the following returnsTrue
:c.isalpha()
,c.isdecimal()
,c.isdigit()
, orc.isnumeric()
.
str.
isalpha
()Return
True
if all characters in the string are alphabetic and there is at least one character,False
otherwise. Alphabetic characters are those characters defined in the Unicode character database as “Letter”, i.e., those with general category property being one of “Lm”, “Lt”, “Lu”, “Ll”, or “Lo”. Note that this is different from the “Alphabetic” property defined in the Unicode Standard.
str.
isascii
()Return
True
if the string is empty or all characters in the string are ASCII,False
otherwise. ASCII characters have code points in the range U+0000-U+007F.New in version 3.7.
str.
isdecimal
()Return
True
if all characters in the string are decimal characters and there is at least one character,False
otherwise. Decimal characters are those that can be used to form numbers in base 10, e.g. U+0660, ARABIC-INDIC DIGIT ZERO. Formally a decimal character is a character in the Unicode General Category “Nd”.
str.
isdigit
()Return
True
if all characters in the string are digits and there is at least one character,False
otherwise. Digits include decimal characters and digits that need special handling, such as the compatibility superscript digits. This covers digits which cannot be used to form numbers in base 10, like the Kharosthi numbers. Formally, a digit is a character that has the property value Numeric_Type=Digit or Numeric_Type=Decimal.
str.
isidentifier
()Return
True
if the string is a valid identifier according to the language definition, section Identifiers and keywords.Call
keyword.iskeyword()
to test whether strings
is a reserved identifier, such asdef
andclass
.Example:
>>>
>>> from keyword import iskeyword >>> 'hello'.isidentifier(), iskeyword('hello') (True, False) >>> 'def'.isidentifier(), iskeyword('def') (True, True)
str.
islower
()Return
True
if all cased characters 4 in the string are lowercase and there is at least one cased character,False
otherwise.
str.
isnumeric
()Return
True
if all characters in the string are numeric characters, and there is at least one character,False
otherwise. Numeric characters include digit characters, and all characters that have the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION ONE FIFTH. Formally, numeric characters are those with the property value Numeric_Type=Digit, Numeric_Type=Decimal or Numeric_Type=Numeric.
str.
isprintable
()Return
True
if all characters in the string are printable or the string is empty,False
otherwise. Nonprintable characters are those characters defined in the Unicode character database as “Other” or “Separator”, excepting the ASCII space (0x20) which is considered printable. (Note that printable characters in this context are those which should not be escaped whenrepr()
is invoked on a string. It has no bearing on the handling of strings written tosys.stdout
orsys.stderr
.)
str.
isspace
()Return
True
if there are only whitespace characters in the string and there is at least one character,False
otherwise.A character is whitespace if in the Unicode character database (see
unicodedata
), either its general category isZs
(“Separator, space”), or its bidirectional class is one ofWS
,B
, orS
.
str.
istitle
()Return
True
if the string is a titlecased string and there is at least one character, for example uppercase characters may only follow uncased characters and lowercase characters only cased ones. ReturnFalse
otherwise.
str.
isupper
()Return
True
if all cased characters 4 in the string are uppercase and there is at least one cased character,False
otherwise.>>>
>>> 'BANANA'.isupper() True >>> 'banana'.isupper() False >>> 'baNana'.isupper() False >>> ' '.isupper() False
str.
join
(iterable)Return a string which is the concatenation of the strings in iterable. A
TypeError
will be raised if there are any non-string values in iterable, includingbytes
objects. The separator between elements is the string providing this method.
str.
ljust
(width[, fillchar])Return the string left justified in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to
len(s)
.
str.
lower
()Return a copy of the string with all the cased characters 4 converted to lowercase.
The lowercasing algorithm used is described in section 3.13 of the Unicode Standard.
str.
lstrip
([chars])Return a copy of the string with leading characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or
None
, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped:>>>
>>> ' spacious '.lstrip() 'spacious ' >>> 'www.example.com'.lstrip('cmowz.') 'example.com'
See
str.removeprefix()
for a method that will remove a single prefix string rather than all of a set of characters. For example:>>>
>>> 'Arthur: three!'.lstrip('Arthur: ') 'ee!' >>> 'Arthur: three!'.removeprefix('Arthur: ') 'three!'
- static
str.
maketrans
(x[, y[, z]]) This static method returns a translation table usable for
str.translate()
.If there is only one argument, it must be a dictionary mapping Unicode ordinals (integers) or characters (strings of length 1) to Unicode ordinals, strings (of arbitrary lengths) or
None
. Character keys will then be converted to ordinals.If there are two arguments, they must be strings of equal length, and in the resulting dictionary, each character in x will be mapped to the character at the same position in y. If there is a third argument, it must be a string, whose characters will be mapped to
None
in the result.
str.
partition
(sep)Split the string at the first occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself, and the part after the separator. If the separator is not found, return a 3-tuple containing the string itself, followed by two empty strings.
str.
removeprefix
(prefix, /)If the string starts with the prefix string, return
string[len(prefix):]
. Otherwise, return a copy of the original string:>>>
>>> 'TestHook'.removeprefix('Test') 'Hook' >>> 'BaseTestCase'.removeprefix('Test') 'BaseTestCase'
New in version 3.9.
str.
removesuffix
(suffix, /)If the string ends with the suffix string and that suffix is not empty, return
string[:-len(suffix)]
. Otherwise, return a copy of the original string:>>>
>>> 'MiscTests'.removesuffix('Tests') 'Misc' >>> 'TmpDirMixin'.removesuffix('Tests') 'TmpDirMixin'
New in version 3.9.
str.
replace
(old, new[, count])Return a copy of the string with all occurrences of substring old replaced by new. If the optional argument count is given, only the first count occurrences are replaced.
str.
rfind
(sub[, start[, end]])Return the highest index in the string where substring sub is found, such that sub is contained within
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
on failure.
str.
rindex
(sub[, start[, end]])Like
rfind()
but raisesValueError
when the substring sub is not found.
str.
rjust
(width[, fillchar])Return the string right justified in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to
len(s)
.
str.
rpartition
(sep)Split the string at the last occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself, and the part after the separator. If the separator is not found, return a 3-tuple containing two empty strings, followed by the string itself.
str.
rsplit
(sep=None, maxsplit=– 1)Return a list of the words in the string, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done, the rightmost ones. If sep is not specified or
None
, any whitespace string is a separator. Except for splitting from the right,rsplit()
behaves likesplit()
which is described in detail below.
str.
rstrip
([chars])Return a copy of the string with trailing characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or
None
, the chars argument defaults to removing whitespace. The chars argument is not a suffix; rather, all combinations of its values are stripped:>>>
>>> ' spacious '.rstrip() ' spacious' >>> 'mississippi'.rstrip('ipz') 'mississ'
See
str.removesuffix()
for a method that will remove a single suffix string rather than all of a set of characters. For example:>>>
>>> 'Monty Python'.rstrip(' Python') 'M' >>> 'Monty Python'.removesuffix(' Python') 'Monty'
str.
split
(sep=None, maxsplit=– 1)Return a list of the words in the string, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done (thus, the list will have at most
maxsplit+1
elements). If maxsplit is not specified or-1
, then there is no limit on the number of splits (all possible splits are made).If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty strings (for example,
'1,,2'.split(',')
returns['1', '', '2']
). The sep argument may consist of multiple characters (for example,'1<>2<>3'.split('<>')
returns['1', '2', '3']
). Splitting an empty string with a specified separator returns['']
.For example:
>>>
>>> '1,2,3'.split(',') ['1', '2', '3'] >>> '1,2,3'.split(',', maxsplit=1) ['1', '2,3'] >>> '1,2,,3,'.split(',') ['1', '2', '', '3', '']
If sep is not specified or is
None
, a different splitting algorithm is applied: runs of consecutive whitespace are regarded as a single separator, and the result will contain no empty strings at the start or end if the string has leading or trailing whitespace. Consequently, splitting an empty string or a string consisting of just whitespace with aNone
separator returns[]
.For example:
>>>
>>> '1 2 3'.split() ['1', '2', '3'] >>> '1 2 3'.split(maxsplit=1) ['1', '2 3'] >>> ' 1 2 3 '.split() ['1', '2', '3']
str.
splitlines
(keepends=False)Return a list of the lines in the string, breaking at line boundaries. Line breaks are not included in the resulting list unless keepends is given and true.
This method splits on the following line boundaries. In particular, the boundaries are a superset of universal newlines.
Representation
Description
\n
Line Feed
\r
Carriage Return
\r\n
Carriage Return + Line Feed
\v
or\x0b
Line Tabulation
\f
or\x0c
Form Feed
\x1c
File Separator
\x1d
Group Separator
\x1e
Record Separator
\x85
Next Line (C1 Control Code)
\u2028
Line Separator
\u2029
Paragraph Separator
Changed in version 3.2:
\v
and\f
added to list of line boundaries.For example:
>>>
>>> 'ab c\n\nde fg\rkl\r\n'.splitlines() ['ab c', '', 'de fg', 'kl'] >>> 'ab c\n\nde fg\rkl\r\n'.splitlines(keepends=True) ['ab c\n', '\n', 'de fg\r', 'kl\r\n']
Unlike
split()
when a delimiter string sep is given, this method returns an empty list for the empty string, and a terminal line break does not result in an extra line:>>>
>>> "".splitlines() [] >>> "One line\n".splitlines() ['One line']
For comparison,
split('\n')
gives:>>>
>>> ''.split('\n') [''] >>> 'Two lines\n'.split('\n') ['Two lines', '']
str.
startswith
(prefix[, start[, end]])Return
True
if string starts with the prefix, otherwise returnFalse
. prefix can also be a tuple of prefixes to look for. With optional start, test string beginning at that position. With optional end, stop comparing string at that position.
str.
strip
([chars])Return a copy of the string with the leading and trailing characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or
None
, the chars argument defaults to removing whitespace. The chars argument is not a prefix or suffix; rather, all combinations of its values are stripped:>>>
>>> ' spacious '.strip() 'spacious' >>> 'www.example.com'.strip('cmowz.') 'example'
The outermost leading and trailing chars argument values are stripped from the string. Characters are removed from the leading end until reaching a string character that is not contained in the set of characters in chars. A similar action takes place on the trailing end. For example:
>>>
>>> comment_string = '#....... Section 3.2.1 Issue #32 .......' >>> comment_string.strip('.#! ') 'Section 3.2.1 Issue #32'
str.
swapcase
()Return a copy of the string with uppercase characters converted to lowercase and vice versa. Note that it is not necessarily true that
s.swapcase().swapcase() == s
.
str.
title
()Return a titlecased version of the string where words start with an uppercase character and the remaining characters are lowercase.
For example:
>>>
>>> 'Hello world'.title() 'Hello World'
The algorithm uses a simple language-independent definition of a word as groups of consecutive letters. The definition works in many contexts but it means that apostrophes in contractions and possessives form word boundaries, which may not be the desired result:
>>>
>>> "they're bill's friends from the UK".title() "They'Re Bill'S Friends From The Uk"
The
string.capwords()
function does not have this problem, as it splits words on spaces only.Alternatively, a workaround for apostrophes can be constructed using regular expressions:
>>>
>>> import re >>> def titlecase(s): ... return re.sub(r"[A-Za-z]+('[A-Za-z]+)?", ... lambda mo: mo.group(0).capitalize(), ... s) ... >>> titlecase("they're bill's friends.") "They're Bill's Friends."
str.
translate
(table)Return a copy of the string in which each character has been mapped through the given translation table. The table must be an object that implements indexing via
__getitem__()
, typically a mapping or sequence. When indexed by a Unicode ordinal (an integer), the table object can do any of the following: return a Unicode ordinal or a string, to map the character to one or more other characters; returnNone
, to delete the character from the return string; or raise aLookupError
exception, to map the character to itself.You can use
str.maketrans()
to create a translation map from character-to-character mappings in different formats.See also the
codecs
module for a more flexible approach to custom character mappings.
str.
upper
()Return a copy of the string with all the cased characters 4 converted to uppercase. Note that
s.upper().isupper()
might beFalse
ifs
contains uncased characters or if the Unicode category of the resulting character(s) is not “Lu” (Letter, uppercase), but e.g. “Lt” (Letter, titlecase).The uppercasing algorithm used is described in section 3.13 of the Unicode Standard.
str.
zfill
(width)Return a copy of the string left filled with ASCII
'0'
digits to make a string of length width. A leading sign prefix ('+'
/'-'
) is handled by inserting the padding after the sign character rather than before. The original string is returned if width is less than or equal tolen(s)
.For example:
>>>
>>> "42".zfill(5) '00042' >>> "-42".zfill(5) '-0042'
printf
-style String Formatting
Note
The formatting operations described here exhibit a variety of quirks that lead to a number of common errors (such as failing to display tuples and dictionaries correctly). Using the newer formatted string literals, the str.format()
interface, or template strings may help avoid these errors. Each of these alternatives provides their own trade-offs and benefits of simplicity, flexibility, and/or extensibility.
String objects have one unique built-in operation: the %
operator (modulo). This is also known as the string formatting or interpolation operator. Given format % values
(where format is a string), %
conversion specifications in format are replaced with zero or more elements of values. The effect is similar to using the sprintf()
in the C language.
If format requires a single argument, values may be a single non-tuple object. 5 Otherwise, values must be a tuple with exactly the number of items specified by the format string, or a single mapping object (for example, a dictionary).
A conversion specifier contains two or more characters and has the following components, which must occur in this order:
The
'%'
character, which marks the start of the specifier.Mapping key (optional), consisting of a parenthesised sequence of characters (for example,
(somename)
).Conversion flags (optional), which affect the result of some conversion types.
Minimum field width (optional). If specified as an
'*'
(asterisk), the actual width is read from the next element of the tuple in values, and the object to convert comes after the minimum field width and optional precision.Precision (optional), given as a
'.'
(dot) followed by the precision. If specified as'*'
(an asterisk), the actual precision is read from the next element of the tuple in values, and the value to convert comes after the precision.Length modifier (optional).
Conversion type.
When the right argument is a dictionary (or other mapping type), then the formats in the string must include a parenthesised mapping key into that dictionary inserted immediately after the '%'
character. The mapping key selects the value to be formatted from the mapping. For example:
>>>
>>> print('%(language)s has %(number)03d quote types.' %
... {'language': "Python", "number": 2})
Python has 002 quote types.
In this case no *
specifiers may occur in a format (since they require a sequential parameter list).
The conversion flag characters are:
Flag | Meaning |
---|---|
| The value conversion will use the “alternate form” (where defined below). |
| The conversion will be zero padded for numeric values. |
| The converted value is left adjusted (overrides the |
| (a space) A blank should be left before a positive number (or empty string) produced by a signed conversion. |
| A sign character ( |
A length modifier (h
, l
, or L
) may be present, but is ignored as it is not necessary for Python – so e.g. %ld
is identical to %d
.
The conversion types are:
Conversion | Meaning | Notes |
---|---|---|
| Signed integer decimal. | |
| Signed integer decimal. | |
| Signed octal value. | (1) |
| Obsolete type – it is identical to | (6) |
| Signed hexadecimal (lowercase). | (2) |
| Signed hexadecimal (uppercase). | (2) |
| Floating point exponential format (lowercase). | (3) |
| Floating point exponential format (uppercase). | (3) |
| Floating point decimal format. | (3) |
| Floating point decimal format. | (3) |
| Floating point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. | (4) |
| Floating point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. | (4) |
| Single character (accepts integer or single character string). | |
| String (converts any Python object using | (5) |
| String (converts any Python object using | (5) |
| String (converts any Python object using | (5) |
| No argument is converted, results in a |
Notes:
The alternate form causes a leading octal specifier (
'0o'
) to be inserted before the first digit.The alternate form causes a leading
'0x'
or'0X'
(depending on whether the'x'
or'X'
format was used) to be inserted before the first digit.The alternate form causes the result to always contain a decimal point, even if no digits follow it.
The precision determines the number of digits after the decimal point and defaults to 6.
The alternate form causes the result to always contain a decimal point, and trailing zeroes are not removed as they would otherwise be.
The precision determines the number of significant digits before and after the decimal point and defaults to 6.
If precision is
N
, the output is truncated toN
characters.See PEP 237.
Since Python strings have an explicit length, %s
conversions do not assume that '\0'
is the end of the string.
Changed in version 3.1: %f
conversions for numbers whose absolute value is over 1e50 are no longer replaced by %g
conversions.
Binary Sequence Types — bytes
, bytearray
, memoryview
The core built-in types for manipulating binary data are bytes
and bytearray
. They are supported by memoryview
which uses the buffer protocol to access the memory of other binary objects without needing to make a copy.
The array
module supports efficient storage of basic data types like 32-bit integers and IEEE754 double-precision floating values.
Bytes Objects
Bytes objects are immutable sequences of single bytes. Since many major binary protocols are based on the ASCII text encoding, bytes objects offer several methods that are only valid when working with ASCII compatible data and are closely related to string objects in a variety of other ways.
- class
bytes
([source[, encoding[, errors]]]) Firstly, the syntax for bytes literals is largely the same as that for string literals, except that a
b
prefix is added:Single quotes:
b'still allows embedded "double" quotes'
Double quotes:
b"still allows embedded 'single' quotes"
Triple quoted:
b'''3 single quotes'''
,b"""3 double quotes"""
Only ASCII characters are permitted in bytes literals (regardless of the declared source code encoding). Any binary values over 127 must be entered into bytes literals using the appropriate escape sequence.
As with string literals, bytes literals may also use a
r
prefix to disable processing of escape sequences. See String and Bytes literals for more about the various forms of bytes literal, including supported escape sequences.While bytes literals and representations are based on ASCII text, bytes objects actually behave like immutable sequences of integers, with each value in the sequence restricted such that
0 <= x < 256
(attempts to violate this restriction will triggerValueError
). This is done deliberately to emphasise that while many binary formats include ASCII based elements and can be usefully manipulated with some text-oriented algorithms, this is not generally the case for arbitrary binary data (blindly applying text processing algorithms to binary data formats that are not ASCII compatible will usually lead to data corruption).In addition to the literal forms, bytes objects can be created in a number of other ways:
A zero-filled bytes object of a specified length:
bytes(10)
From an iterable of integers:
bytes(range(20))
Copying existing binary data via the buffer protocol:
bytes(obj)
Also see the bytes built-in.
Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data. Accordingly, the bytes type has an additional class method to read data in that format:
- classmethod
fromhex
(string) This
bytes
class method returns a bytes object, decoding the given string object. The string must contain two hexadecimal digits per byte, with ASCII whitespace being ignored.>>>
>>> bytes.fromhex('2Ef0 F1f2 ') b'.\xf0\xf1\xf2'
Changed in version 3.7:
bytes.fromhex()
now skips all ASCII whitespace in the string, not just spaces.
A reverse conversion function exists to transform a bytes object into its hexadecimal representation.
hex
([sep[, bytes_per_sep]])Return a string object containing two hexadecimal digits for each byte in the instance.
>>>
>>> b'\xf0\xf1\xf2'.hex() 'f0f1f2'
If you want to make the hex string easier to read, you can specify a single character separator sep parameter to include in the output. By default between each byte. A second optional bytes_per_sep parameter controls the spacing. Positive values calculate the separator position from the right, negative values from the left.
>>>
>>> value = b'\xf0\xf1\xf2' >>> value.hex('-') 'f0-f1-f2' >>> value.hex('_', 2) 'f0_f1f2' >>> b'UUDDLRLRAB'.hex(' ', -4) '55554444 4c524c52 4142'
New in version 3.5.
Changed in version 3.8:
bytes.hex()
now supports optional sep and bytes_per_sep parameters to insert separators between bytes in the hex output.
Since bytes objects are sequences of integers (akin to a tuple), for a bytes object b, b[0]
will be an integer, while b[0:1]
will be a bytes object of length 1. (This contrasts with text strings, where both indexing and slicing will produce a string of length 1)
The representation of bytes objects uses the literal format (b'...'
) since it is often more useful than e.g. bytes([46, 46, 46])
. You can always convert a bytes object into a list of integers using list(b)
.
Note
For Python 2.x users: In the Python 2.x series, a variety of implicit conversions between 8-bit strings (the closest thing 2.x offers to a built-in binary data type) and Unicode strings were permitted. This was a backwards compatibility workaround to account for the fact that Python originally only supported 8-bit text, and Unicode text was a later addition. In Python 3.x, those implicit conversions are gone – conversions between 8-bit binary data and Unicode text must be explicit, and bytes and string objects will always compare unequal.
Bytearray Objects
bytearray
objects are a mutable counterpart to bytes
objects.
- class
bytearray
([source[, encoding[, errors]]]) There is no dedicated literal syntax for bytearray objects, instead they are always created by calling the constructor:
Creating an empty instance:
bytearray()
Creating a zero-filled instance with a given length:
bytearray(10)
From an iterable of integers:
bytearray(range(20))
Copying existing binary data via the buffer protocol:
bytearray(b'Hi!')
As bytearray objects are mutable, they support the mutable sequence operations in addition to the common bytes and bytearray operations described in Bytes and Bytearray Operations.
Also see the bytearray built-in.
Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data. Accordingly, the bytearray type has an additional class method to read data in that format:
- classmethod
fromhex
(string) This
bytearray
class method returns bytearray object, decoding the given string object. The string must contain two hexadecimal digits per byte, with ASCII whitespace being ignored.>>>
>>> bytearray.fromhex('2Ef0 F1f2 ') bytearray(b'.\xf0\xf1\xf2')
Changed in version 3.7:
bytearray.fromhex()
now skips all ASCII whitespace in the string, not just spaces.
A reverse conversion function exists to transform a bytearray object into its hexadecimal representation.
hex
([sep[, bytes_per_sep]])Return a string object containing two hexadecimal digits for each byte in the instance.
>>>
>>> bytearray(b'\xf0\xf1\xf2').hex() 'f0f1f2'
New in version 3.5.
Changed in version 3.8: Similar to
bytes.hex()
,bytearray.hex()
now supports optional sep and bytes_per_sep parameters to insert separators between bytes in the hex output.
Since bytearray objects are sequences of integers (akin to a list), for a bytearray object b, b[0]
will be an integer, while b[0:1]
will be a bytearray object of length 1. (This contrasts with text strings, where both indexing and slicing will produce a string of length 1)
The representation of bytearray objects uses the bytes literal format (bytearray(b'...')
) since it is often more useful than e.g. bytearray([46, 46, 46])
. You can always convert a bytearray object into a list of integers using list(b)
.
Bytes and Bytearray Operations
Both bytes and bytearray objects support the common sequence operations. They interoperate not just with operands of the same type, but with any bytes-like object. Due to this flexibility, they can be freely mixed in operations without causing errors. However, the return type of the result may depend on the order of operands.
Note
The methods on bytes and bytearray objects don’t accept strings as their arguments, just as the methods on strings don’t accept bytes as their arguments. For example, you have to write:
a = "abc"
b = a.replace("a", "f")
and:
a = b"abc"
b = a.replace(b"a", b"f")
Some bytes and bytearray operations assume the use of ASCII compatible binary formats, and hence should be avoided when working with arbitrary binary data. These restrictions are covered below.
Note
Using these ASCII based operations to manipulate binary data that is not stored in an ASCII based format may lead to data corruption.
The following methods on bytes and bytearray objects can be used with arbitrary binary data.
bytes.
count
(sub[, start[, end]])bytearray.
count
(sub[, start[, end]])Return the number of non-overlapping occurrences of subsequence sub in the range [start, end]. Optional arguments start and end are interpreted as in slice notation.
The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
bytes.
removeprefix
(prefix, /)bytearray.
removeprefix
(prefix, /)If the binary data starts with the prefix string, return
bytes[len(prefix):]
. Otherwise, return a copy of the original binary data:>>>
>>> b'TestHook'.removeprefix(b'Test') b'Hook' >>> b'BaseTestCase'.removeprefix(b'Test') b'BaseTestCase'
The prefix may be any bytes-like object.
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
New in version 3.9.
bytes.
removesuffix
(suffix, /)bytearray.
removesuffix
(suffix, /)If the binary data ends with the suffix string and that suffix is not empty, return
bytes[:-len(suffix)]
. Otherwise, return a copy of the original binary data:>>>
>>> b'MiscTests'.removesuffix(b'Tests') b'Misc' >>> b'TmpDirMixin'.removesuffix(b'Tests') b'TmpDirMixin'
The suffix may be any bytes-like object.
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
New in version 3.9.
bytes.
decode
(encoding=‘utf-8’, errors=‘strict’)bytearray.
decode
(encoding=‘utf-8’, errors=‘strict’)Return a string decoded from the given bytes. Default encoding is
'utf-8'
. errors may be given to set a different error handling scheme. The default for errors is'strict'
, meaning that encoding errors raise aUnicodeError
. Other possible values are'ignore'
,'replace'
and any other name registered viacodecs.register_error()
, see section Error Handlers. For a list of possible encodings, see section Standard Encodings.By default, the errors argument is not checked for best performances, but only used at the first decoding error. Enable the Python Development Mode, or use a debug build to check errors.
Note
Passing the encoding argument to
str
allows decoding any bytes-like object directly, without needing to make a temporary bytes or bytearray object.Changed in version 3.1: Added support for keyword arguments.
Changed in version 3.9: The errors is now checked in development mode and in debug mode.
bytes.
endswith
(suffix[, start[, end]])bytearray.
endswith
(suffix[, start[, end]])Return
True
if the binary data ends with the specified suffix, otherwise returnFalse
. suffix can also be a tuple of suffixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.The suffix(es) to search for may be any bytes-like object.
bytes.
find
(sub[, start[, end]])bytearray.
find
(sub[, start[, end]])Return the lowest index in the data where the subsequence sub is found, such that sub is contained in the slice
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
if sub is not found.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Note
The
find()
method should be used only if you need to know the position of sub. To check if sub is a substring or not, use thein
operator:>>>
>>> b'Py' in b'Python' True
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
bytes.
index
(sub[, start[, end]])bytearray.
index
(sub[, start[, end]])Like
find()
, but raiseValueError
when the subsequence is not found.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
bytes.
join
(iterable)bytearray.
join
(iterable)Return a bytes or bytearray object which is the concatenation of the binary data sequences in iterable. A
TypeError
will be raised if there are any values in iterable that are not bytes-like objects, includingstr
objects. The separator between elements is the contents of the bytes or bytearray object providing this method.
- static
bytes.
maketrans
(from, to) - static
bytearray.
maketrans
(from, to) This static method returns a translation table usable for
bytes.translate()
that will map each character in from into the character at the same position in to; from and to must both be bytes-like objects and have the same length.New in version 3.1.
bytes.
partition
(sep)bytearray.
partition
(sep)Split the sequence at the first occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself or its bytearray copy, and the part after the separator. If the separator is not found, return a 3-tuple containing a copy of the original sequence, followed by two empty bytes or bytearray objects.
The separator to search for may be any bytes-like object.
bytes.
replace
(old, new[, count])bytearray.
replace
(old, new[, count])Return a copy of the sequence with all occurrences of subsequence old replaced by new. If the optional argument count is given, only the first count occurrences are replaced.
The subsequence to search for and its replacement may be any bytes-like object.
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
rfind
(sub[, start[, end]])bytearray.
rfind
(sub[, start[, end]])Return the highest index in the sequence where the subsequence sub is found, such that sub is contained within
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
on failure.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
bytes.
rindex
(sub[, start[, end]])bytearray.
rindex
(sub[, start[, end]])Like
rfind()
but raisesValueError
when the subsequence sub is not found.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
bytes.
rpartition
(sep)bytearray.
rpartition
(sep)Split the sequence at the last occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself or its bytearray copy, and the part after the separator. If the separator is not found, return a 3-tuple containing two empty bytes or bytearray objects, followed by a copy of the original sequence.
The separator to search for may be any bytes-like object.
bytes.
startswith
(prefix[, start[, end]])bytearray.
startswith
(prefix[, start[, end]])Return
True
if the binary data starts with the specified prefix, otherwise returnFalse
. prefix can also be a tuple of prefixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.The prefix(es) to search for may be any bytes-like object.
bytes.
translate
(table, /, delete=b”)bytearray.
translate
(table, /, delete=b”)Return a copy of the bytes or bytearray object where all bytes occurring in the optional argument delete are removed, and the remaining bytes have been mapped through the given translation table, which must be a bytes object of length 256.
You can use the
bytes.maketrans()
method to create a translation table.Set the table argument to
None
for translations that only delete characters:>>>
>>> b'read this short text'.translate(None, b'aeiou') b'rd ths shrt txt'
Changed in version 3.6: delete is now supported as a keyword argument.
The following methods on bytes and bytearray objects have default behaviours that assume the use of ASCII compatible binary formats, but can still be used with arbitrary binary data by passing appropriate arguments. Note that all of the bytearray methods in this section do not operate in place, and instead produce new objects.
bytes.
center
(width[, fillbyte])bytearray.
center
(width[, fillbyte])Return a copy of the object centered in a sequence of length width. Padding is done using the specified fillbyte (default is an ASCII space). For
bytes
objects, the original sequence is returned if width is less than or equal tolen(s)
.Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
ljust
(width[, fillbyte])bytearray.
ljust
(width[, fillbyte])Return a copy of the object left justified in a sequence of length width. Padding is done using the specified fillbyte (default is an ASCII space). For
bytes
objects, the original sequence is returned if width is less than or equal tolen(s)
.Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
lstrip
([chars])bytearray.
lstrip
([chars])Return a copy of the sequence with specified leading bytes removed. The chars argument is a binary sequence specifying the set of byte values to be removed – the name refers to the fact this method is usually used with ASCII characters. If omitted or
None
, the chars argument defaults to removing ASCII whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped:>>>
>>> b' spacious '.lstrip() b'spacious ' >>> b'www.example.com'.lstrip(b'cmowz.') b'example.com'
The binary sequence of byte values to remove may be any bytes-like object. See
removeprefix()
for a method that will remove a single prefix string rather than all of a set of characters. For example:>>>
>>> b'Arthur: three!'.lstrip(b'Arthur: ') b'ee!' >>> b'Arthur: three!'.removeprefix(b'Arthur: ') b'three!'
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
rjust
(width[, fillbyte])bytearray.
rjust
(width[, fillbyte])Return a copy of the object right justified in a sequence of length width. Padding is done using the specified fillbyte (default is an ASCII space). For
bytes
objects, the original sequence is returned if width is less than or equal tolen(s)
.Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
rsplit
(sep=None, maxsplit=– 1)bytearray.
rsplit
(sep=None, maxsplit=– 1)Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done, the rightmost ones. If sep is not specified or
None
, any subsequence consisting solely of ASCII whitespace is a separator. Except for splitting from the right,rsplit()
behaves likesplit()
which is described in detail below.
bytes.
rstrip
([chars])bytearray.
rstrip
([chars])Return a copy of the sequence with specified trailing bytes removed. The chars argument is a binary sequence specifying the set of byte values to be removed – the name refers to the fact this method is usually used with ASCII characters. If omitted or
None
, the chars argument defaults to removing ASCII whitespace. The chars argument is not a suffix; rather, all combinations of its values are stripped:>>>
>>> b' spacious '.rstrip() b' spacious' >>> b'mississippi'.rstrip(b'ipz') b'mississ'
The binary sequence of byte values to remove may be any bytes-like object. See
removesuffix()
for a method that will remove a single suffix string rather than all of a set of characters. For example:>>>
>>> b'Monty Python'.rstrip(b' Python') b'M' >>> b'Monty Python'.removesuffix(b' Python') b'Monty'
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
split
(sep=None, maxsplit=– 1)bytearray.
split
(sep=None, maxsplit=– 1)Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given and non-negative, at most maxsplit splits are done (thus, the list will have at most
maxsplit+1
elements). If maxsplit is not specified or is-1
, then there is no limit on the number of splits (all possible splits are made).If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty subsequences (for example,
b'1,,2'.split(b',')
returns[b'1', b'', b'2']
). The sep argument may consist of a multibyte sequence (for example,b'1<>2<>3'.split(b'<>')
returns[b'1', b'2', b'3']
). Splitting an empty sequence with a specified separator returns[b'']
or[bytearray(b'')]
depending on the type of object being split. The sep argument may be any bytes-like object.For example:
>>>
>>> b'1,2,3'.split(b',') [b'1', b'2', b'3'] >>> b'1,2,3'.split(b',', maxsplit=1) [b'1', b'2,3'] >>> b'1,2,,3,'.split(b',') [b'1', b'2', b'', b'3', b'']
If sep is not specified or is
None
, a different splitting algorithm is applied: runs of consecutive ASCII whitespace are regarded as a single separator, and the result will contain no empty strings at the start or end if the sequence has leading or trailing whitespace. Consequently, splitting an empty sequence or a sequence consisting solely of ASCII whitespace without a specified separator returns[]
.For example:
>>>
>>> b'1 2 3'.split() [b'1', b'2', b'3'] >>> b'1 2 3'.split(maxsplit=1) [b'1', b'2 3'] >>> b' 1 2 3 '.split() [b'1', b'2', b'3']
bytes.
strip
([chars])bytearray.
strip
([chars])Return a copy of the sequence with specified leading and trailing bytes removed. The chars argument is a binary sequence specifying the set of byte values to be removed – the name refers to the fact this method is usually used with ASCII characters. If omitted or
None
, the chars argument defaults to removing ASCII whitespace. The chars argument is not a prefix or suffix; rather, all combinations of its values are stripped:>>>
>>> b' spacious '.strip() b'spacious' >>> b'www.example.com'.strip(b'cmowz.') b'example'
The binary sequence of byte values to remove may be any bytes-like object.
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
The following methods on bytes and bytearray objects assume the use of ASCII compatible binary formats and should not be applied to arbitrary binary data. Note that all of the bytearray methods in this section do not operate in place, and instead produce new objects.
bytes.
capitalize
()bytearray.
capitalize
()Return a copy of the sequence with each byte interpreted as an ASCII character, and the first byte capitalized and the rest lowercased. Non-ASCII byte values are passed through unchanged.
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
expandtabs
(tabsize=8)bytearray.
expandtabs
(tabsize=8)Return a copy of the sequence where all ASCII tab characters are replaced by one or more ASCII spaces, depending on the current column and the given tab size. Tab positions occur every tabsize bytes (default is 8, giving tab positions at columns 0, 8, 16 and so on). To expand the sequence, the current column is set to zero and the sequence is examined byte by byte. If the byte is an ASCII tab character (
b'\t'
), one or more space characters are inserted in the result until the current column is equal to the next tab position. (The tab character itself is not copied.) If the current byte is an ASCII newline (b'\n'
) or carriage return (b'\r'
), it is copied and the current column is reset to zero. Any other byte value is copied unchanged and the current column is incremented by one regardless of how the byte value is represented when printed:>>>
>>> b'01\t012\t0123\t01234'.expandtabs() b'01 012 0123 01234' >>> b'01\t012\t0123\t01234'.expandtabs(4) b'01 012 0123 01234'
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
isalnum
()bytearray.
isalnum
()Return
True
if all bytes in the sequence are alphabetical ASCII characters or ASCII decimal digits and the sequence is not empty,False
otherwise. Alphabetic ASCII characters are those byte values in the sequenceb'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
. ASCII decimal digits are those byte values in the sequenceb'0123456789'
.For example:
>>>
>>> b'ABCabc1'.isalnum() True >>> b'ABC abc1'.isalnum() False
bytes.
isalpha
()bytearray.
isalpha
()Return
True
if all bytes in the sequence are alphabetic ASCII characters and the sequence is not empty,False
otherwise. Alphabetic ASCII characters are those byte values in the sequenceb'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
.For example:
>>>
>>> b'ABCabc'.isalpha() True >>> b'ABCabc1'.isalpha() False
bytes.
isascii
()bytearray.
isascii
()Return
True
if the sequence is empty or all bytes in the sequence are ASCII,False
otherwise. ASCII bytes are in the range 0-0x7F.New in version 3.7.
bytes.
isdigit
()bytearray.
isdigit
()Return
True
if all bytes in the sequence are ASCII decimal digits and the sequence is not empty,False
otherwise. ASCII decimal digits are those byte values in the sequenceb'0123456789'
.For example:
>>>
>>> b'1234'.isdigit() True >>> b'1.23'.isdigit() False
bytes.
islower
()bytearray.
islower
()Return
True
if there is at least one lowercase ASCII character in the sequence and no uppercase ASCII characters,False
otherwise.For example:
>>>
>>> b'hello world'.islower() True >>> b'Hello world'.islower() False
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.
bytes.
isspace
()bytearray.
isspace
()Return
True
if all bytes in the sequence are ASCII whitespace and the sequence is not empty,False
otherwise. ASCII whitespace characters are those byte values in the sequenceb' \t\n\r\x0b\f'
(space, tab, newline, carriage return, vertical tab, form feed).
bytes.
istitle
()bytearray.
istitle
()Return
True
if the sequence is ASCII titlecase and the sequence is not empty,False
otherwise. Seebytes.title()
for more details on the definition of “titlecase”.For example:
>>>
>>> b'Hello World'.istitle() True >>> b'Hello world'.istitle() False
bytes.
isupper
()bytearray.
isupper
()Return
True
if there is at least one uppercase alphabetic ASCII character in the sequence and no lowercase ASCII characters,False
otherwise.For example:
>>>
>>> b'HELLO WORLD'.isupper() True >>> b'Hello world'.isupper() False
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.
bytes.
lower
()bytearray.
lower
()Return a copy of the sequence with all the uppercase ASCII characters converted to their corresponding lowercase counterpart.
For example:
>>>
>>> b'Hello World'.lower() b'hello world'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
splitlines
(keepends=False)bytearray.
splitlines
(keepends=False)Return a list of the lines in the binary sequence, breaking at ASCII line boundaries. This method uses the universal newlines approach to splitting lines. Line breaks are not included in the resulting list unless keepends is given and true.
For example:
>>>
>>> b'ab c\n\nde fg\rkl\r\n'.splitlines() [b'ab c', b'', b'de fg', b'kl'] >>> b'ab c\n\nde fg\rkl\r\n'.splitlines(keepends=True) [b'ab c\n', b'\n', b'de fg\r', b'kl\r\n']
Unlike
split()
when a delimiter string sep is given, this method returns an empty list for the empty string, and a terminal line break does not result in an extra line:>>>
>>> b"".split(b'\n'), b"Two lines\n".split(b'\n') ([b''], [b'Two lines', b'']) >>> b"".splitlines(), b"One line\n".splitlines() ([], [b'One line'])
bytes.
swapcase
()bytearray.
swapcase
()Return a copy of the sequence with all the lowercase ASCII characters converted to their corresponding uppercase counterpart and vice-versa.
For example:
>>>
>>> b'Hello World'.swapcase() b'hELLO wORLD'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.Unlike
str.swapcase()
, it is always the case thatbin.swapcase().swapcase() == bin
for the binary versions. Case conversions are symmetrical in ASCII, even though that is not generally true for arbitrary Unicode code points.Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
title
()bytearray.
title
()Return a titlecased version of the binary sequence where words start with an uppercase ASCII character and the remaining characters are lowercase. Uncased byte values are left unmodified.
For example:
>>>
>>> b'Hello world'.title() b'Hello World'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
. All other byte values are uncased.The algorithm uses a simple language-independent definition of a word as groups of consecutive letters. The definition works in many contexts but it means that apostrophes in contractions and possessives form word boundaries, which may not be the desired result:
>>>
>>> b"they're bill's friends from the UK".title() b"They'Re Bill'S Friends From The Uk"
A workaround for apostrophes can be constructed using regular expressions:
>>>
>>> import re >>> def titlecase(s): ... return re.sub(rb"[A-Za-z]+('[A-Za-z]+)?", ... lambda mo: mo.group(0)[0:1].upper() + ... mo.group(0)[1:].lower(), ... s) ... >>> titlecase(b"they're bill's friends.") b"They're Bill's Friends."
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
upper
()bytearray.
upper
()Return a copy of the sequence with all the lowercase ASCII characters converted to their corresponding uppercase counterpart.
For example:
>>>
>>> b'Hello World'.upper() b'HELLO WORLD'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
bytes.
zfill
(width)bytearray.
zfill
(width)Return a copy of the sequence left filled with ASCII
b'0'
digits to make a sequence of length width. A leading sign prefix (b'+'
/b'-'
) is handled by inserting the padding after the sign character rather than before. Forbytes
objects, the original sequence is returned if width is less than or equal tolen(seq)
.For example:
>>>
>>> b"42".zfill(5) b'00042' >>> b"-42".zfill(5) b'-0042'
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
printf
-style Bytes Formatting
Note
The formatting operations described here exhibit a variety of quirks that lead to a number of common errors (such as failing to display tuples and dictionaries correctly). If the value being printed may be a tuple or dictionary, wrap it in a tuple.
Bytes objects (bytes
/bytearray
) have one unique built-in operation: the %
operator (modulo). This is also known as the bytes formatting or interpolation operator. Given format % values
(where format is a bytes object), %
conversion specifications in format are replaced with zero or more elements of values. The effect is similar to using the sprintf()
in the C language.
If format requires a single argument, values may be a single non-tuple object. 5 Otherwise, values must be a tuple with exactly the number of items specified by the format bytes object, or a single mapping object (for example, a dictionary).
A conversion specifier contains two or more characters and has the following components, which must occur in this order:
The
'%'
character, which marks the start of the specifier.Mapping key (optional), consisting of a parenthesised sequence of characters (for example,
(somename)
).Conversion flags (optional), which affect the result of some conversion types.
Minimum field width (optional). If specified as an
'*'
(asterisk), the actual width is read from the next element of the tuple in values, and the object to convert comes after the minimum field width and optional precision.Precision (optional), given as a
'.'
(dot) followed by the precision. If specified as'*'
(an asterisk), the actual precision is read from the next element of the tuple in values, and the value to convert comes after the precision.Length modifier (optional).
Conversion type.
When the right argument is a dictionary (or other mapping type), then the formats in the bytes object must include a parenthesised mapping key into that dictionary inserted immediately after the '%'
character. The mapping key selects the value to be formatted from the mapping. For example:
>>>
>>> print(b'%(language)s has %(number)03d quote types.' %
... {b'language': b"Python", b"number": 2})
b'Python has 002 quote types.'
In this case no *
specifiers may occur in a format (since they require a sequential parameter list).
The conversion flag characters are:
Flag | Meaning |
---|---|
| The value conversion will use the “alternate form” (where defined below). |
| The conversion will be zero padded for numeric values. |
| The converted value is left adjusted (overrides the |
| (a space) A blank should be left before a positive number (or empty string) produced by a signed conversion. |
| A sign character ( |
A length modifier (h
, l
, or L
) may be present, but is ignored as it is not necessary for Python – so e.g. %ld
is identical to %d
.
The conversion types are:
Conversion | Meaning | Notes |
---|---|---|
| Signed integer decimal. | |
| Signed integer decimal. | |
| Signed octal value. | (1) |
| Obsolete type – it is identical to | (8) |
| Signed hexadecimal (lowercase). | (2) |
| Signed hexadecimal (uppercase). | (2) |
| Floating point exponential format (lowercase). | (3) |
| Floating point exponential format (uppercase). | (3) |
| Floating point decimal format. | (3) |
| Floating point decimal format. | (3) |
| Floating point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. | (4) |
| Floating point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. | (4) |
| Single byte (accepts integer or single byte objects). | |
| Bytes (any object that follows the buffer protocol or has | (5) |
|
| (6) |
| Bytes (converts any Python object using | (5) |
|
| (7) |
| No argument is converted, results in a |
Notes:
The alternate form causes a leading octal specifier (
'0o'
) to be inserted before the first digit.The alternate form causes a leading
'0x'
or'0X'
(depending on whether the'x'
or'X'
format was used) to be inserted before the first digit.The alternate form causes the result to always contain a decimal point, even if no digits follow it.
The precision determines the number of digits after the decimal point and defaults to 6.
The alternate form causes the result to always contain a decimal point, and trailing zeroes are not removed as they would otherwise be.
The precision determines the number of significant digits before and after the decimal point and defaults to 6.
If precision is
N
, the output is truncated toN
characters.b'%s'
is deprecated, but will not be removed during the 3.x series.b'%r'
is deprecated, but will not be removed during the 3.x series.See PEP 237.
Note
The bytearray version of this method does not operate in place – it always produces a new object, even if no changes were made.
See also
PEP 461 – Adding % formatting to bytes and bytearray
New in version 3.5.
Memory Views
memoryview
objects allow Python code to access the internal data of an object that supports the buffer protocol without copying.
- class
memoryview
(object) Create a
memoryview
that references object. object must support the buffer protocol. Built-in objects that support the buffer protocol includebytes
andbytearray
.A
memoryview
has the notion of an element, which is the atomic memory unit handled by the originating object. For many simple types such asbytes
andbytearray
, an element is a single byte, but other types such asarray.array
may have bigger elements.len(view)
is equal to the length oftolist
. Ifview.ndim = 0
, the length is 1. Ifview.ndim = 1
, the length is equal to the number of elements in the view. For higher dimensions, the length is equal to the length of the nested list representation of the view. Theitemsize
attribute will give you the number of bytes in a single element.A
memoryview
supports slicing and indexing to expose its data. One-dimensional slicing will result in a subview:>>>
>>> v = memoryview(b'abcefg') >>> v[1] 98 >>> v[-1] 103 >>> v[1:4] >>> bytes(v[1:4]) b'bce'
If
format
is one of the native format specifiers from thestruct
module, indexing with an integer or a tuple of integers is also supported and returns a single element with the correct type. One-dimensional memoryviews can be indexed with an integer or a one-integer tuple. Multi-dimensional memoryviews can be indexed with tuples of exactly ndim integers where ndim is the number of dimensions. Zero-dimensional memoryviews can be indexed with the empty tuple.Here is an example with a non-byte format:
>>>
>>> import array >>> a = array.array('l', [-11111111, 22222222, -33333333, 44444444]) >>> m = memoryview(a) >>> m[0] -11111111 >>> m[-1] 44444444 >>> m[::2].tolist() [-11111111, -33333333]
If the underlying object is writable, the memoryview supports one-dimensional slice assignment. Resizing is not allowed:
>>>
>>> data = bytearray(b'abcefg') >>> v = memoryview(data) >>> v.readonly False >>> v[0] = ord(b'z') >>> data bytearray(b'zbcefg') >>> v[1:4] = b'123' >>> data bytearray(b'z123fg') >>> v[2:3] = b'spam' Traceback (most recent call last): File "", line 1, in ValueError: memoryview assignment: lvalue and rvalue have different structures >>> v[2:6] = b'spam' >>> data bytearray(b'z1spam')
One-dimensional memoryviews of hashable (read-only) types with formats ‘B’, ‘b’ or ‘c’ are also hashable. The hash is defined as
hash(m) == hash(m.tobytes())
:>>>
>>> v = memoryview(b'abcefg') >>> hash(v) == hash(b'abcefg') True >>> hash(v[2:4]) == hash(b'ce') True >>> hash(v[::-2]) == hash(b'abcefg'[::-2]) True
Changed in version 3.3: One-dimensional memoryviews can now be sliced. One-dimensional memoryviews with formats ‘B’, ‘b’ or ‘c’ are now hashable.
Changed in version 3.4: memoryview is now registered automatically with
collections.abc.Sequence
Changed in version 3.5: memoryviews can now be indexed with tuple of integers.
memoryview
has several methods:__eq__
(exporter)A memoryview and a PEP 3118 exporter are equal if their shapes are equivalent and if all corresponding values are equal when the operands’ respective format codes are interpreted using
struct
syntax.For the subset of
struct
format strings currently supported bytolist()
,v
andw
are equal ifv.tolist() == w.tolist()
:>>>
>>> import array >>> a = array.array('I', [1, 2, 3, 4, 5]) >>> b = array.array('d', [1.0, 2.0, 3.0, 4.0, 5.0]) >>> c = array.array('b', [5, 3, 1]) >>> x = memoryview(a) >>> y = memoryview(b) >>> x == a == y == b True >>> x.tolist() == a.tolist() == y.tolist() == b.tolist() True >>> z = y[::-2] >>> z == c True >>> z.tolist() == c.tolist() True
If either format string is not supported by the
struct
module, then the objects will always compare as unequal (even if the format strings and buffer contents are identical):>>>
>>> from ctypes import BigEndianStructure, c_long >>> class BEPoint(BigEndianStructure): ... _fields_ = [("x", c_long), ("y", c_long)] ... >>> point = BEPoint(100, 200) >>> a = memoryview(point) >>> b = memoryview(point) >>> a == point False >>> a == b False
Note that, as with floating point numbers,
v is w
does not implyv == w
for memoryview objects.Changed in version 3.3: Previous versions compared the raw memory disregarding the item format and the logical array structure.
tobytes
(order=None)Return the data in the buffer as a bytestring. This is equivalent to calling the
bytes
constructor on the memoryview.>>>
>>> m = memoryview(b"abc") >>> m.tobytes() b'abc' >>> bytes(m) b'abc'
For non-contiguous arrays the result is equal to the flattened list representation with all elements converted to bytes.
tobytes()
supports all format strings, including those that are not instruct
module syntax.New in version 3.8: order can be {‘C’, ‘F’, ‘A’}. When order is ‘C’ or ‘F’, the data of the original array is converted to C or Fortran order. For contiguous views, ‘A’ returns an exact copy of the physical memory. In particular, in-memory Fortran order is preserved. For non-contiguous views, the data is converted to C first. order=None is the same as order=’C’.
hex
([sep[, bytes_per_sep]])Return a string object containing two hexadecimal digits for each byte in the buffer.
>>>
>>> m = memoryview(b"abc") >>> m.hex() '616263'
New in version 3.5.
Changed in version 3.8: Similar to
bytes.hex()
,memoryview.hex()
now supports optional sep and bytes_per_sep parameters to insert separators between bytes in the hex output.
tolist
()Return the data in the buffer as a list of elements.
>>>
>>> memoryview(b'abc').tolist() [97, 98, 99] >>> import array >>> a = array.array('d', [1.1, 2.2, 3.3]) >>> m = memoryview(a) >>> m.tolist() [1.1, 2.2, 3.3]
toreadonly
()Return a readonly version of the memoryview object. The original memoryview object is unchanged.
>>>
>>> m = memoryview(bytearray(b'abc')) >>> mm = m.toreadonly() >>> mm.tolist() [89, 98, 99] >>> mm[0] = 42 Traceback (most recent call last): File "", line 1, in TypeError: cannot modify read-only memory >>> m[0] = 43 >>> mm.tolist() [43, 98, 99]
New in version 3.8.
release
()Release the underlying buffer exposed by the memoryview object. Many objects take special actions when a view is held on them (for example, a
bytearray
would temporarily forbid resizing); therefore, calling release() is handy to remove these restrictions (and free any dangling resources) as soon as possible.After this method has been called, any further operation on the view raises a
ValueError
(exceptrelease()
itself which can be called multiple times):>>>
>>> m = memoryview(b'abc') >>> m.release() >>> m[0] Traceback (most recent call last): File "", line 1, in ValueError: operation forbidden on released memoryview object
The context management protocol can be used for a similar effect, using the
with
statement:>>>
>>> with memoryview(b'abc') as m: ... m[0] ... 97 >>> m[0] Traceback (most recent call last): File "", line 1, in ValueError: operation forbidden on released memoryview object
New in version 3.2.
cast
(format[, shape])Cast a memoryview to a new format or shape. shape defaults to
[byte_length//new_itemsize]
, which means that the result view will be one-dimensional. The return value is a new memoryview, but the buffer itself is not copied. Supported casts are 1D -> C-contiguous and C-contiguous -> 1D.The destination format is restricted to a single element native format in
struct
syntax. One of the formats must be a byte format (‘B’, ‘b’ or ‘c’). The byte length of the result must be the same as the original length.Cast 1D/long to 1D/unsigned bytes:
>>>
>>> import array >>> a = array.array('l', [1,2,3]) >>> x = memoryview(a) >>> x.format 'l' >>> x.itemsize 8 >>> len(x) 3 >>> x.nbytes 24 >>> y = x.cast('B') >>> y.format 'B' >>> y.itemsize 1 >>> len(y) 24 >>> y.nbytes 24
Cast 1D/unsigned bytes to 1D/char:
>>>
>>> b = bytearray(b'zyz') >>> x = memoryview(b) >>> x[0] = b'a' Traceback (most recent call last): File "", line 1, in ValueError: memoryview: invalid value for format "B" >>> y = x.cast('c') >>> y[0] = b'a' >>> b bytearray(b'ayz')
Cast 1D/bytes to 3D/ints to 1D/signed char:
>>>
>>> import struct >>> buf = struct.pack("i"*12, *list(range(12))) >>> x = memoryview(buf) >>> y = x.cast('i', shape=[2,2,3]) >>> y.tolist() [[[0, 1, 2], [3, 4, 5]], [[6, 7, 8], [9, 10, 11]]] >>> y.format 'i' >>> y.itemsize 4 >>> len(y) 2 >>> y.nbytes 48 >>> z = y.cast('b') >>> z.format 'b' >>> z.itemsize 1 >>> len(z) 48 >>> z.nbytes 48
Cast 1D/unsigned long to 2D/unsigned long:
>>>
>>> buf = struct.pack("L"*6, *list(range(6))) >>> x = memoryview(buf) >>> y = x.cast('L', shape=[2,3]) >>> len(y) 2 >>> y.nbytes 48 >>> y.tolist() [[0, 1, 2], [3, 4, 5]]
New in version 3.3.
Changed in version 3.5: The source format is no longer restricted when casting to a byte view.
There are also several readonly attributes available:
obj
The underlying object of the memoryview:
>>>
>>> b = bytearray(b'xyz') >>> m = memoryview(b) >>> m.obj is b True
New in version 3.3.
nbytes
nbytes == product(shape) * itemsize == len(m.tobytes())
. This is the amount of space in bytes that the array would use in a contiguous representation. It is not necessarily equal tolen(m)
:>>>
>>> import array >>> a = array.array('i', [1,2,3,4,5]) >>> m = memoryview(a) >>> len(m) 5 >>> m.nbytes 20 >>> y = m[::2] >>> len(y) 3 >>> y.nbytes 12 >>> len(y.tobytes()) 12
Multi-dimensional arrays:
>>>
>>> import struct >>> buf = struct.pack("d"*12, *[1.5*x for x in range(12)]) >>> x = memoryview(buf) >>> y = x.cast('d', shape=[3,4]) >>> y.tolist() [[0.0, 1.5, 3.0, 4.5], [6.0, 7.5, 9.0, 10.5], [12.0, 13.5, 15.0, 16.5]] >>> len(y) 3 >>> y.nbytes 96
New in version 3.3.
readonly
A bool indicating whether the memory is read only.
format
A string containing the format (in
struct
module style) for each element in the view. A memoryview can be created from exporters with arbitrary format strings, but some methods (e.g.tolist()
) are restricted to native single element formats.Changed in version 3.3: format
'B'
is now handled according to the struct module syntax. This means thatmemoryview(b'abc')[0] == b'abc'[0] == 97
.
itemsize
The size in bytes of each element of the memoryview:
>>>
>>> import array, struct >>> m = memoryview(array.array('H', [32000, 32001, 32002])) >>> m.itemsize 2 >>> m[0] 32000 >>> struct.calcsize('H') == m.itemsize True
ndim
An integer indicating how many dimensions of a multi-dimensional array the memory represents.
shape
A tuple of integers the length of
ndim
giving the shape of the memory as an N-dimensional array.Changed in version 3.3: An empty tuple instead of
None
when ndim = 0.
strides
A tuple of integers the length of
ndim
giving the size in bytes to access each element for each dimension of the array.Changed in version 3.3: An empty tuple instead of
None
when ndim = 0.
suboffsets
Used internally for PIL-style arrays. The value is informational only.
c_contiguous
A bool indicating whether the memory is C-contiguous.
New in version 3.3.
f_contiguous
A bool indicating whether the memory is Fortran contiguous.
New in version 3.3.
contiguous
A bool indicating whether the memory is contiguous.
New in version 3.3.
Set Types — set
, frozenset
A set object is an unordered collection of distinct hashable objects. Common uses include membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference. (For other containers see the built-in dict
, list
, and tuple
classes, and the collections
module.)
Like other collections, sets support x in set
, len(set)
, and for x in set
. Being an unordered collection, sets do not record element position or order of insertion. Accordingly, sets do not support indexing, slicing, or other sequence-like behavior.
There are currently two built-in set types, set
and frozenset
. The set
type is mutable — the contents can be changed using methods like add()
and remove()
. Since it is mutable, it has no hash value and cannot be used as either a dictionary key or as an element of another set. The frozenset
type is immutable and hashable — its contents cannot be altered after it is created; it can therefore be used as a dictionary key or as an element of another set.
Non-empty sets (not frozensets) can be created by placing a comma-separated list of elements within braces, for example: {'jack', 'sjoerd'}
, in addition to the set
constructor.
The constructors for both classes work the same:
- class
set
([iterable]) - class
frozenset
([iterable]) Return a new set or frozenset object whose elements are taken from iterable. The elements of a set must be hashable. To represent sets of sets, the inner sets must be
frozenset
objects. If iterable is not specified, a new empty set is returned.Sets can be created by several means:
Use a comma-separated list of elements within braces:
{'jack', 'sjoerd'}
Use a set comprehension:
{c for c in 'abracadabra' if c not in 'abc'}
Use the type constructor:
set()
,set('foobar')
,set(['a', 'b', 'foo'])
Instances of
set
andfrozenset
provide the following operations:len(s)
Return the number of elements in set s (cardinality of s).
x in s
Test x for membership in s.
x not in s
Test x for non-membership in s.
isdisjoint
(other)Return
True
if the set has no elements in common with other. Sets are disjoint if and only if their intersection is the empty set.
issubset
(other)set <= other
Test whether every element in the set is in other.
set < other
Test whether the set is a proper subset of other, that is,
set <= other and set != other
.
issuperset
(other)set >= other
Test whether every element in other is in the set.
set > other
Test whether the set is a proper superset of other, that is,
set >= other and set != other
.
union
(*others)set | other | ...
Return a new set with elements from the set and all others.
intersection
(*others)set & other & ...
Return a new set with elements common to the set and all others.
difference
(*others)set - other - ...
Return a new set with elements in the set that are not in the others.
symmetric_difference
(other)set ^ other
Return a new set with elements in either the set or other but not both.
copy
()Return a shallow copy of the set.
Note, the non-operator versions of
union()
,intersection()
,difference()
,symmetric_difference()
,issubset()
, andissuperset()
methods will accept any iterable as an argument. In contrast, their operator based counterparts require their arguments to be sets. This precludes error-prone constructions likeset('abc') & 'cbs'
in favor of the more readableset('abc').intersection('cbs')
.Both
set
andfrozenset
support set to set comparisons. Two sets are equal if and only if every element of each set is contained in the other (each is a subset of the other). A set is less than another set if and only if the first set is a proper subset of the second set (is a subset, but is not equal). A set is greater than another set if and only if the first set is a proper superset of the second set (is a superset, but is not equal).Instances of
set
are compared to instances offrozenset
based on their members. For example,set('abc') == frozenset('abc')
returnsTrue
and so doesset('abc') in set([frozenset('abc')])
.The subset and equality comparisons do not generalize to a total ordering function. For example, any two nonempty disjoint sets are not equal and are not subsets of each other, so all of the following return
False
:a<b
,a==b
, ora>b
.Since sets only define partial ordering (subset relationships), the output of the
list.sort()
method is undefined for lists of sets.Set elements, like dictionary keys, must be hashable.
Binary operations that mix
set
instances withfrozenset
return the type of the first operand. For example:frozenset('ab') | set('bc')
returns an instance offrozenset
.The following table lists operations available for
set
that do not apply to immutable instances offrozenset
:update
(*others)set |= other | ...
Update the set, adding elements from all others.
intersection_update
(*others)set &= other & ...
Update the set, keeping only elements found in it and all others.
difference_update
(*others)set -= other | ...
Update the set, removing elements found in others.
symmetric_difference_update
(other)set ^= other
Update the set, keeping only elements found in either set, but not in both.
add
(elem)Add element elem to the set.
remove
(elem)Remove element elem from the set. Raises
KeyError
if elem is not contained in the set.
discard
(elem)Remove element elem from the set if it is present.
pop
()Remove and return an arbitrary element from the set. Raises
KeyError
if the set is empty.
clear
()Remove all elements from the set.
Note, the non-operator versions of the
update()
,intersection_update()
,difference_update()
, andsymmetric_difference_update()
methods will accept any iterable as an argument.Note, the elem argument to the
__contains__()
,remove()
, anddiscard()
methods may be a set. To support searching for an equivalent frozenset, a temporary one is created from elem.
Mapping Types — dict
A mapping object maps hashable values to arbitrary objects. Mappings are mutable objects. There is currently only one standard mapping type, the dictionary. (For other containers see the built-in list
, set
, and tuple
classes, and the collections
module.)
A dictionary’s keys are almost arbitrary values. Values that are not hashable, that is, values containing lists, dictionaries or other mutable types (that are compared by value rather than by object identity) may not be used as keys. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (such as 1
and 1.0
) then they can be used interchangeably to index the same dictionary entry. (Note however, that since computers store floating-point numbers as approximations it is usually unwise to use them as dictionary keys.)
- class
dict
(**kwargs) - class
dict
(mapping, **kwargs) - class
dict
(iterable, **kwargs) Return a new dictionary initialized from an optional positional argument and a possibly empty set of keyword arguments.
Dictionaries can be created by several means:
Use a comma-separated list of
key: value
pairs within braces:{'jack': 4098, 'sjoerd': 4127}
or{4098: 'jack', 4127: 'sjoerd'}
Use a dict comprehension:
{}
,{x: x ** 2 for x in range(10)}
Use the type constructor:
dict()
,dict([('foo', 100), ('bar', 200)])
,dict(foo=100, bar=200)
If no positional argument is given, an empty dictionary is created. If a positional argument is given and it is a mapping object, a dictionary is created with the same key-value pairs as the mapping object. Otherwise, the positional argument must be an iterable object. Each item in the iterable must itself be an iterable with exactly two objects. The first object of each item becomes a key in the new dictionary, and the second object the corresponding value. If a key occurs more than once, the last value for that key becomes the corresponding value in the new dictionary.
If keyword arguments are given, the keyword arguments and their values are added to the dictionary created from the positional argument. If a key being added is already present, the value from the keyword argument replaces the value from the positional argument.
To illustrate, the following examples all return a dictionary equal to
{"one": 1, "two": 2, "three": 3}
:>>>
>>> a = dict(one=1, two=2, three=3) >>> b = {'one': 1, 'two': 2, 'three': 3} >>> c = dict(zip(['one', 'two', 'three'], [1, 2, 3])) >>> d = dict([('two', 2), ('one', 1), ('three', 3)]) >>> e = dict({'three': 3, 'one': 1, 'two': 2}) >>> f = dict({'one': 1, 'three': 3}, two=2) >>> a == b == c == d == e == f True
Providing keyword arguments as in the first example only works for keys that are valid Python identifiers. Otherwise, any valid keys can be used.
These are the operations that dictionaries support (and therefore, custom mapping types should support too):
list(d)
Return a list of all the keys used in the dictionary d.
len(d)
Return the number of items in the dictionary d.
d[key]
Return the item of d with key key. Raises a
KeyError
if key is not in the map.If a subclass of dict defines a method
__missing__()
and key is not present, thed[key]
operation calls that method with the key key as argument. Thed[key]
operation then returns or raises whatever is returned or raised by the__missing__(key)
call. No other operations or methods invoke__missing__()
. If__missing__()
is not defined,KeyError
is raised.__missing__()
must be a method; it cannot be an instance variable:>>>
>>> class Counter(dict): ... def __missing__(self, key): ... return 0 >>> c = Counter() >>> c['red'] 0 >>> c['red'] += 1 >>> c['red'] 1
The example above shows part of the implementation of
collections.Counter
. A different__missing__
method is used bycollections.defaultdict
.
d[key] = value
Set
d[key]
to value.
del d[key]
Remove
d[key]
from d. Raises aKeyError
if key is not in the map.
key in d
Return
True
if d has a key key, elseFalse
.
key not in d
Equivalent to
not key in d
.
iter(d)
Return an iterator over the keys of the dictionary. This is a shortcut for
iter(d.keys())
.
clear
()Remove all items from the dictionary.
copy
()Return a shallow copy of the dictionary.
- classmethod
fromkeys
(iterable[, value]) Create a new dictionary with keys from iterable and values set to value.
fromkeys()
is a class method that returns a new dictionary. value defaults toNone
. All of the values refer to just a single instance, so it generally doesn’t make sense for value to be a mutable object such as an empty list. To get distinct values, use a dict comprehension instead.
get
(key[, default])Return the value for key if key is in the dictionary, else default. If default is not given, it defaults to
None
, so that this method never raises aKeyError
.
items
()Return a new view of the dictionary’s items (
(key, value)
pairs). See the documentation of view objects.
keys
()Return a new view of the dictionary’s keys. See the documentation of view objects.
pop
(key[, default])If key is in the dictionary, remove it and return its value, else return default. If default is not given and key is not in the dictionary, a
KeyError
is raised.
popitem
()Remove and return a
(key, value)
pair from the dictionary. Pairs are returned in LIFO order.popitem()
is useful to destructively iterate over a dictionary, as often used in set algorithms. If the dictionary is empty, callingpopitem()
raises aKeyError
.Changed in version 3.7: LIFO order is now guaranteed. In prior versions,
popitem()
would return an arbitrary key/value pair.
reversed(d)
Return a reverse iterator over the keys of the dictionary. This is a shortcut for
reversed(d.keys())
.New in version 3.8.
setdefault
(key[, default])If key is in the dictionary, return its value. If not, insert key with a value of default and return default. default defaults to
None
.
update
([other])Update the dictionary with the key/value pairs from other, overwriting existing keys. Return
None
.update()
accepts either another dictionary object or an iterable of key/value pairs (as tuples or other iterables of length two). If keyword arguments are specified, the dictionary is then updated with those key/value pairs:d.update(red=1, blue=2)
.
values
()Return a new view of the dictionary’s values. See the documentation of view objects.
An equality comparison between one
dict.values()
view and another will always returnFalse
. This also applies when comparingdict.values()
to itself:>>>
>>> d = {'a': 1} >>> d.values() == d.values() False
d | other
Create a new dictionary with the merged keys and values of d and other, which must both be dictionaries. The values of other take priority when d and other share keys.
New in version 3.9.
d |= other
Update the dictionary d with keys and values from other, which may be either a mapping or an iterable of key/value pairs. The values of other take priority when d and other share keys.
New in version 3.9.
Dictionaries compare equal if and only if they have the same
(key, value)
pairs (regardless of ordering). Order comparisons (‘<’, ‘<=’, ‘>=’, ‘>’) raiseTypeError
.Dictionaries preserve insertion order. Note that updating a key does not affect the order. Keys added after deletion are inserted at the end.
>>>
>>> d = {"one": 1, "two": 2, "three": 3, "four": 4} >>> d {'one': 1, 'two': 2, 'three': 3, 'four': 4} >>> list(d) ['one', 'two', 'three', 'four'] >>> list(d.values()) [1, 2, 3, 4] >>> d["one"] = 42 >>> d {'one': 42, 'two': 2, 'three': 3, 'four': 4} >>> del d["two"] >>> d["two"] = None >>> d {'one': 42, 'three': 3, 'four': 4, 'two': None}
Changed in version 3.7: Dictionary order is guaranteed to be insertion order. This behavior was an implementation detail of CPython from 3.6.
Dictionaries and dictionary views are reversible.
>>>
>>> d = {"one": 1, "two": 2, "three": 3, "four": 4} >>> d {'one': 1, 'two': 2, 'three': 3, 'four': 4} >>> list(reversed(d)) ['four', 'three', 'two', 'one'] >>> list(reversed(d.values())) [4, 3, 2, 1] >>> list(reversed(d.items())) [('four', 4), ('three', 3), ('two', 2), ('one', 1)]
Changed in version 3.8: Dictionaries are now reversible.
See also
types.MappingProxyType
can be used to create a read-only view of a dict
.
Dictionary view objects
The objects returned by dict.keys()
, dict.values()
and dict.items()
are view objects. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes.
Dictionary views can be iterated over to yield their respective data, and support membership tests:
len(dictview)
Return the number of entries in the dictionary.
iter(dictview)
Return an iterator over the keys, values or items (represented as tuples of
(key, value)
) in the dictionary.Keys and values are iterated over in insertion order. This allows the creation of
(value, key)
pairs usingzip()
:pairs = zip(d.values(), d.keys())
. Another way to create the same list ispairs = [(v, k) for (k, v) in d.items()]
.Iterating views while adding or deleting entries in the dictionary may raise a
RuntimeError
or fail to iterate over all entries.Changed in version 3.7: Dictionary order is guaranteed to be insertion order.
x in dictview
Return
True
if x is in the underlying dictionary’s keys, values or items (in the latter case, x should be a(key, value)
tuple).
reversed(dictview)
Return a reverse iterator over the keys, values or items of the dictionary. The view will be iterated in reverse order of the insertion.
Changed in version 3.8: Dictionary views are now reversible.
dictview.mapping
Return a
types.MappingProxyType
that wraps the original dictionary to which the view refers.New in version 3.10.
Keys views are set-like since their entries are unique and hashable. If all values are hashable, so that (key, value)
pairs are unique and hashable, then the items view is also set-like. (Values views are not treated as set-like since the entries are generally not unique.) For set-like views, all of the operations defined for the abstract base class collections.abc.Set
are available (for example, ==
, <
, or ^
).
An example of dictionary view usage:
>>>
>>> dishes = {'eggs': 2, 'sausage': 1, 'bacon': 1, 'spam': 500}
>>> keys = dishes.keys()
>>> values = dishes.values()
>>> # iteration
>>> n = 0
>>> for val in values:
... n += val
>>> print(n)
504
>>> # keys and values are iterated over in the same order (insertion order)
>>> list(keys)
['eggs', 'sausage', 'bacon', 'spam']
>>> list(values)
[2, 1, 1, 500]
>>> # view objects are dynamic and reflect dict changes
>>> del dishes['eggs']
>>> del dishes['sausage']
>>> list(keys)
['bacon', 'spam']
>>> # set operations
>>> keys & {'eggs', 'bacon', 'salad'}
{'bacon'}
>>> keys ^ {'sausage', 'juice'}
{'juice', 'sausage', 'bacon', 'spam'}
>>> # get back a read-only proxy for the original dictionary
>>> values.mapping
mappingproxy({'eggs': 2, 'sausage': 1, 'bacon': 1, 'spam': 500})
>>> values.mapping['spam']
500
Context Manager Types
Python’s with
statement supports the concept of a runtime context defined by a context manager. This is implemented using a pair of methods that allow user-defined classes to define a runtime context that is entered before the statement body is executed and exited when the statement ends:
contextmanager.
__enter__
()Enter the runtime context and return either this object or another object related to the runtime context. The value returned by this method is bound to the identifier in the
as
clause ofwith
statements using this context manager.An example of a context manager that returns itself is a file object. File objects return themselves from __enter__() to allow
open()
to be used as the context expression in awith
statement.An example of a context manager that returns a related object is the one returned by
decimal.localcontext()
. These managers set the active decimal context to a copy of the original decimal context and then return the copy. This allows changes to be made to the current decimal context in the body of thewith
statement without affecting code outside thewith
statement.
contextmanager.
__exit__
(exc_type, exc_val, exc_tb)Exit the runtime context and return a Boolean flag indicating if any exception that occurred should be suppressed. If an exception occurred while executing the body of the
with
statement, the arguments contain the exception type, value and traceback information. Otherwise, all three arguments areNone
.Returning a true value from this method will cause the
with
statement to suppress the exception and continue execution with the statement immediately following thewith
statement. Otherwise the exception continues propagating after this method has finished executing. Exceptions that occur during execution of this method will replace any exception that occurred in the body of thewith
statement.The exception passed in should never be reraised explicitly – instead, this method should return a false value to indicate that the method completed successfully and does not want to suppress the raised exception. This allows context management code to easily detect whether or not an
__exit__()
method has actually failed.
Python defines several context managers to support easy thread synchronisation, prompt closure of files or other objects, and simpler manipulation of the active decimal arithmetic context. The specific types are not treated specially beyond their implementation of the context management protocol. See the contextlib
module for some examples.
Python’s generators and the contextlib.contextmanager
decorator provide a convenient way to implement these protocols. If a generator function is decorated with the contextlib.contextmanager
decorator, it will return a context manager implementing the necessary __enter__()
and __exit__()
methods, rather than the iterator produced by an undecorated generator function.
Note that there is no specific slot for any of these methods in the type structure for Python objects in the Python/C API. Extension types wanting to define these methods must provide them as a normal Python accessible method. Compared to the overhead of setting up the runtime context, the overhead of a single class dictionary lookup is negligible.
Type Annotation Types — Generic Alias, Union
The core built-in types for type annotations are Generic Alias and Union.
Generic Alias Type
GenericAlias
objects are generally created by subscripting a class. They are most often used with container classes, such as list
or dict
. For example, list[int]
is a GenericAlias
object created by subscripting the list
class with the argument int
. GenericAlias
objects are intended primarily for use with type annotations.
Note
It is generally only possible to subscript a class if the class implements the special method __class_getitem__()
.
A GenericAlias
object acts as a proxy for a generic type, implementing parameterized generics.
For a container class, the argument(s) supplied to a subscription of the class may indicate the type(s) of the elements an object contains. For example, set[bytes]
can be used in type annotations to signify a set
in which all the elements are of type bytes
.
For a class which defines __class_getitem__()
but is not a container, the argument(s) supplied to a subscription of the class will often indicate the return type(s) of one or more methods defined on an object. For example, regular expressions
can be used on both the str
data type and the bytes
data type:
If
x = re.search('foo', 'foo')
,x
will be a re.Match object where the return values ofx.group(0)
andx[0]
will both be of typestr
. We can represent this kind of object in type annotations with theGenericAlias
re.Match[str]
.If
y = re.search(b'bar', b'bar')
, (note theb
forbytes
),y
will also be an instance ofre.Match
, but the return values ofy.group(0)
andy[0]
will both be of typebytes
. In type annotations, we would represent this variety of re.Match objects withre.Match[bytes]
.
GenericAlias
objects are instances of the class types.GenericAlias
, which can also be used to create GenericAlias
objects directly.
T[X, Y, ...]
Creates a
GenericAlias
representing a typeT
parameterized by types X, Y, and more depending on theT
used. For example, a function expecting alist
containingfloat
elements:def average(values: list[float]) -> float: return sum(values) / len(values)
Another example for mapping objects, using a
dict
, which is a generic type expecting two type parameters representing the key type and the value type. In this example, the function expects adict
with keys of typestr
and values of typeint
:def send_post_request(url: str, body: dict[str, int]) -> None: ...
The builtin functions isinstance()
and issubclass()
do not accept GenericAlias
types for their second argument:
>>>
>>> isinstance([1, 2], list[str])
Traceback (most recent call last):
File "", line 1, in
TypeError: isinstance() argument 2 cannot be a parameterized generic
The Python runtime does not enforce type annotations. This extends to generic types and their type parameters. When creating a container object from a GenericAlias
, the elements in the container are not checked against their type. For example, the following code is discouraged, but will run without errors:
>>>
>>> t = list[str]
>>> t([1, 2, 3])
[1, 2, 3]
Furthermore, parameterized generics erase type parameters during object creation:
>>>
>>> t = list[str]
>>> type(t)
<class 'types.GenericAlias'>
>>> l = t()
>>> type(l)
<class 'list'>
Calling repr()
or str()
on a generic shows the parameterized type:
>>>
>>> repr(list[int])
'list[int]'
>>> str(list[int])
'list[int]'
The __getitem__()
method of generic containers will raise an exception to disallow mistakes like dict[str][str]
:
>>>
>>> dict[str][str]
Traceback (most recent call last):
File "", line 1, in
TypeError: There are no type variables left in dict[str]
However, such expressions are valid when type variables are used. The index must have as many elements as there are type variable items in the GenericAlias
object’s __args__
.
>>>
>>> from typing import TypeVar
>>> Y = TypeVar('Y')
>>> dict[str, Y][int]
dict[str, int]
Standard Generic Classes
The following standard library classes support parameterized generics. This list is non-exhaustive.
Special Attributes of GenericAlias
objects
All parameterized generics implement special read-only attributes.
genericalias.
__origin__
This attribute points at the non-parameterized generic class:
>>>
>>> list[int].__origin__ <class 'list'>
genericalias.
__args__
This attribute is a
tuple
(possibly of length 1) of generic types passed to the original__class_getitem__()
of the generic class:>>>
>>> dict[str, list[int]].__args__ (<class 'str'>, list[int])
genericalias.
__parameters__
This attribute is a lazily computed tuple (possibly empty) of unique type variables found in
__args__
:>>>
>>> from typing import TypeVar >>> T = TypeVar('T') >>> list[T].__parameters__ (~T,)
Note
A
GenericAlias
object withtyping.ParamSpec
parameters may not have correct__parameters__
after substitution becausetyping.ParamSpec
is intended primarily for static type checking.
See also
- PEP 484 – Type Hints
Introducing Python’s framework for type annotations.
- PEP 585 – Type Hinting Generics In Standard Collections
Introducing the ability to natively parameterize standard-library classes, provided they implement the special class method
__class_getitem__()
.- Generics, user-defined generics and
typing.Generic
Documentation on how to implement generic classes that can be parameterized at runtime and understood by static type-checkers.
New in version 3.9.
Union Type
A union object holds the value of the |
(bitwise or) operation on multiple type objects. These types are intended primarily for type annotations. The union type expression enables cleaner type hinting syntax compared to typing.Union
.
X | Y | ...
Defines a union object which holds types X, Y, and so forth.
X | Y
means either X or Y. It is equivalent totyping.Union[X, Y]
. For example, the following function expects an argument of typeint
orfloat
:def square(number: int | float) -> int | float: return number ** 2
union_object == other
Union objects can be tested for equality with other union objects. Details:
Unions of unions are flattened:
(int | str) | float == int | str | float
Redundant types are removed:
int | str | int == int | str
When comparing unions, the order is ignored:
int | str == str | int
It is compatible with
typing.Union
:int | str == typing.Union[int, str]
Optional types can be spelled as a union with
None
:str | None == typing.Optional[str]
isinstance(obj, union_object)
issubclass(obj, union_object)
Calls to
isinstance()
andissubclass()
are also supported with a union object:>>>
>>> isinstance("", int | str) True
However, union objects containing parameterized generics cannot be used:
>>>
>>> isinstance(1, int | list[int]) Traceback (most recent call last): File "", line 1, in TypeError: isinstance() argument 2 cannot contain a parameterized generic
The user-exposed type for the union object can be accessed from types.UnionType
and used for isinstance()
checks. An object cannot be instantiated from the type:
>>>
>>> import types
>>> isinstance(int | str, types.UnionType)
True
>>> types.UnionType()
Traceback (most recent call last):
File "", line 1, in
TypeError: cannot create 'types.UnionType' instances
Note
The __or__()
method for type objects was added to support the syntax X | Y
. If a metaclass implements __or__()
, the Union may override it:
>>>
>>> class M(type):
... def __or__(self, other):
... return "Hello"
...
>>> class C(metaclass=M):
... pass
...
>>> C | int
'Hello'
>>> int | C
int | __main__.C
See also
PEP 604 – PEP proposing the X | Y
syntax and the Union type.
New in version 3.10.
Other Built-in Types
The interpreter supports several other kinds of objects. Most of these support only one or two operations.
Modules
The only special operation on a module is attribute access: m.name
, where m is a module and name accesses a name defined in m’s symbol table. Module attributes can be assigned to. (Note that the import
statement is not, strictly speaking, an operation on a module object; import foo
does not require a module object named foo to exist, rather it requires an (external) definition for a module named foo somewhere.)
A special attribute of every module is __dict__
. This is the dictionary containing the module’s symbol table. Modifying this dictionary will actually change the module’s symbol table, but direct assignment to the __dict__
attribute is not possible (you can write m.__dict__['a'] = 1
, which defines m.a
to be 1
, but you can’t write m.__dict__ = {}
). Modifying __dict__
directly is not recommended.
Modules built into the interpreter are written like this: <module 'sys' (built-in)>
. If loaded from a file, they are written as <module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>
.
Classes and Class Instances
See Objects, values and types and Class definitions for these.
Functions
Function objects are created by function definitions. The only operation on a function object is to call it: func(argument-list)
.
There are really two flavors of function objects: built-in functions and user-defined functions. Both support the same operation (to call the function), but the implementation is different, hence the different object types.
See Function definitions for more information.
Methods
Methods are functions that are called using the attribute notation. There are two flavors: built-in methods (such as append()
on lists) and class instance methods. Built-in methods are described with the types that support them.
If you access a method (a function defined in a class namespace) through an instance, you get a special object: a bound method (also called instance method) object. When called, it will add the self
argument to the argument list. Bound methods have two special read-only attributes: m.__self__
is the object on which the method operates, and m.__func__
is the function implementing the method. Calling m(arg-1, arg-2, ..., arg-n)
is completely equivalent to calling m.__func__(m.__self__, arg-1, arg-2, ..., arg-n)
.
Like function objects, bound method objects support getting arbitrary attributes. However, since method attributes are actually stored on the underlying function object (meth.__func__
), setting method attributes on bound methods is disallowed. Attempting to set an attribute on a method results in an AttributeError
being raised. In order to set a method attribute, you need to explicitly set it on the underlying function object:
>>>
>>> class C:
... def method(self):
... pass
...
>>> c = C()
>>> c.method.whoami = 'my name is method' # can't set on the method
Traceback (most recent call last):
File "", line 1, in
AttributeError: 'method' object has no attribute 'whoami'
>>> c.
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