Built-in Types — Python 3.14.4 documentation

Built-in Types — Python 3.14.4 documentation
index
modules
next
previous
Python
3.14.4 Documentation
The Python Standard Library
Built-in Types
Theme
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.
If one of the methods raises an
exception when called, the exception is propagated and the object does
not have a truth value (for example,
NotImplemented
).
Here are most of the built-in objects considered false:
constants defined to be false:
None
and
False
zero of any numeric type:
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
or
False
for false and
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
or
if
is true, then
, else
(1)
and
if
is false, then
, else
(2)
not
if
is false, then
True
else
False
(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, so
not
==
is
interpreted as
not
(a
==
b)
, and
==
not
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,
<=
is equivalent to
and
<=
, except that
is evaluated only once (but in both cases
is not
evaluated at all when
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
is
object identity
is
not
negated object identity
Unless stated otherwise, objects of different 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
, 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.
The constructors
int()
float()
, and
complex()
can be used to produce numbers of a specific type.
Python fully supports mixed arithmetic: when a binary arithmetic operator has
operands of different built-in numeric types, the operand with the “narrower”
type is widened to that of the other:
If both arguments are complex numbers, no conversion is performed;
if either argument is a complex or a floating-point number, the other is
converted to a floating-point number;
otherwise, both must be integers and no conversion is necessary.
Arithmetic with complex and real operands is defined by the usual mathematical
formula, for example:
complex
complex
complex
complex
A comparison between numbers of different types behaves as though the exact
values of those numbers were being compared.
All numeric types (except complex) support the following operations (for priorities of
the operations, see
Operator precedence
):
Operation
Result
Notes
Full documentation
sum of
and
difference of
and
product of
and
quotient of
and
//
floored quotient of
and
(1)(2)
remainder of
(2)
-x
negated
+x
unchanged
abs(x)
absolute value or magnitude of
abs()
int(x)
converted to integer
(3)(6)
int()
float(x)
converted to floating point
(4)(6)
float()
complex(re,
im)
a complex number with real part
re
, imaginary part
im
im
defaults to zero.
(6)
complex()
c.conjugate()
conjugate of the complex number
divmod(x,
y)
the pair
(x
//
y,
y)
(2)
divmod()
pow(x,
y)
to the power
(5)
pow()
**
to the power
(5)
Notes:
Also referred to as integer division. For operands of type
int
the result has type
int
. For operands of type
float
the result has type
float
. In general, the result is a whole
integer, though the result’s type is not necessarily
int
. The result is
always rounded towards minus infinity:
1//2
is
(-1)//2
is
-1
1//(-2)
is
-1
, and
(-1)//(-2)
is
Not for complex numbers. Instead convert to floats using
abs()
if
appropriate.
Conversion from
float
to
int
truncates, discarding the
fractional part. See functions
math.floor()
and
math.ceil()
for
alternative 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)
and
**
to be
, as is common for
programming languages.
The numeric literals accepted include the digits
to
or any
Unicode equivalent (code points with the
Nd
property).
See
the Unicode Standard
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
math.trunc(x)
truncated to
Integral
round(x[,
n])
rounded to
digits,
rounding half to even. If
is
omitted, it defaults to 0.
math.floor(x)
the greatest
Integral
<=
math.ceil(x)
the least
Integral
>=
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
and
(4)
bitwise
exclusive or
of
and
(4)
bitwise
and
of
and
(4)
<<
shifted left by
bits
(1)(2)
>>
shifted right by
bits
(1)(3)
~x
the bits of
inverted
Notes:
Negative shift counts are illegal and cause a
ValueError
to be raised.
A left shift by
bits is equivalent to multiplication by
pow(2,
n)
A right shift by
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
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:
>>>
37
>>>
bin
'-0b100101'
>>>
bit_length
()
More precisely, if
is nonzero, then
x.bit_length()
is the
unique positive integer
such that
2**(k-1)
<=
abs(x)
2**k
Equivalently, when
abs(x)
is small enough to have a correctly
rounded logarithm, then
int(log(abs(x),
2))
If
is zero, then
x.bit_length()
returns
Equivalent to:
def
bit_length
self
):
bin
self
# binary representation: bin(-37) --> '-0b100101'
lstrip
'-0b'
# remove leading zeros and minus sign
return
len
# len('100101') --> 6
Added 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:
>>>
19
>>>
bin
'0b10011'
>>>
bit_count
()
>>>
bit_count
()
Equivalent to:
def
bit_count
self
):
return
bin
self
count
"1"
Added in version 3.10.
int.
to_bytes
length
byteorder
'big'
signed
False
Return an array of bytes representing an integer.
>>>
1024
to_bytes
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'
>>>
1000
>>>
to_bytes
((
bit_length
()
//
byteorder
'little'
b'\xe8\x03'
The integer is represented using
length
bytes, and defaults to 1. 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, and defaults to
"big"
. 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.
The
signed
argument determines whether two’s complement is used to
represent the integer. If
signed
is
False
and a negative integer is
given, an
OverflowError
is raised. The default value for
signed
is
False
The default values can be used to conveniently turn an integer into a
single byte object:
>>>
65
to_bytes
()
b'A'
However, when using the default arguments, don’t try
to convert a value greater than 255 or you’ll get an
OverflowError
Equivalent to:
def
to_bytes
length
byteorder
'big'
signed
False
):
if
byteorder
==
'little'
order
range
length
elif
byteorder
==
'big'
order
reversed
range
length
))
else
raise
ValueError
"byteorder must be either 'little' or 'big'"
return
bytes
((
>>
0xff
for
in
order
Added in version 3.2.
Changed in version 3.11:
Added default argument values for
length
and
byteorder
classmethod
int.
from_bytes
bytes
byteorder
'big'
signed
False
Return the integer represented by the given array of bytes.
>>>
int
from_bytes
\x00\x10
byteorder
'big'
16
>>>
int
from_bytes
\x00\x10
byteorder
'little'
4096
>>>
int
from_bytes
\xfc\x00
byteorder
'big'
signed
True
-1024
>>>
int
from_bytes
\xfc\x00
byteorder
'big'
signed
False
64512
>>>
int
from_bytes
([
255
],
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, and defaults to
"big"
. 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, use
sys.byteorder
as the byte order value.
The
signed
argument indicates whether two’s complement is used to
represent the integer.
Equivalent to:
def
from_bytes
bytes
byteorder
'big'
signed
False
):
if
byteorder
==
'little'
little_ordered
list
bytes
elif
byteorder
==
'big'
little_ordered
list
reversed
bytes
))
else
raise
ValueError
"byteorder must be either 'little' or 'big'"
sum
<<
for
in
enumerate
little_ordered
))
if
signed
and
little_ordered
and
little_ordered
0x80
):
-=
<<
len
little_ordered
return
Added in version 3.2.
Changed in version 3.11:
Added default argument value for
byteorder
int.
as_integer_ratio
Return a pair of integers whose ratio is equal to the original
integer and has a positive denominator. The integer ratio of integers
(whole numbers) is always the integer as the numerator and
as the
denominator.
Added in version 3.8.
int.
is_integer
Returns
True
. Exists for duck type compatibility with
float.is_integer()
Added in version 3.12.
Additional Methods on Float
The float type implements the
numbers.Real
abstract base
class
. float also has the following additional methods.
classmethod
float.
from_number
Class method to return a floating-point number constructed from a number
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
float.from_number(x)
delegates to
x.__float__()
If
__float__()
is not defined then it falls back
to
__index__()
Added in version 3.14.
float.
as_integer_ratio
Return a pair of integers whose ratio is exactly equal to the
original float. The ratio is in lowest terms and has a positive denominator. Raises
OverflowError
on infinities and a
ValueError
on
NaNs.
float.
is_integer
Return
True
if the float instance is finite with integral
value, and
False
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 trailing
and
exponent.
classmethod
float.
fromhex
Class method to return the float represented by a hexadecimal
string
. The string
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'
Additional Methods on Complex
The
complex
type implements the
numbers.Complex
abstract base class
complex
also has the following additional methods.
classmethod
complex.
from_number
Class method to convert a number to a complex number.
For a general Python object
complex.from_number(x)
delegates to
x.__complex__()
. If
__complex__()
is not defined then it falls back
to
__float__()
. If
__float__()
is not defined then it falls back
to
__index__()
Added in version 3.14.
Hashing of numeric types
For numbers
and
, possibly of different types, it’s a requirement
that
hash(x)
==
hash(y)
whenever
==
(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
for a fixed prime
. The value of
is
made available to Python as the
modulus
attribute of
sys.hash_info
CPython implementation detail:
Currently, the prime used is
2**31
on machines with 32-bit C
longs and
2**61
on machines with 64-bit C longs.
Here are the rules in detail:
If
is a nonnegative rational number and
is not divisible
by
, define
hash(x)
as
invmod(n,
P)
, where
invmod(n,
P)
gives the inverse of
modulo
If
is a nonnegative rational number and
is
divisible by
(but
is not) then
has no inverse
modulo
and the rule above doesn’t apply; in this case define
hash(x)
to be the constant value
sys.hash_info.inf
If
is a negative rational number define
hash(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
number
, the hash values of the real
and imaginary parts are combined by computing
hash(z.real)
sys.hash_info.imag
hash(z.imag)
, reduced modulo
2**sys.hash_info.width
so that it lies in
range(-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
):
"""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)).
"""
sys
hash_info
modulus
# Remove common factors of P. (Unnecessary if m and n already coprime.)
while
==
==
//
//
if
==
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
pow
if
hash_value
hash_value
if
hash_value
==
hash_value
return
hash_value
def
hash_float
):
"""Compute the hash of a float x."""
if
math
isnan
):
return
object
__hash__
elif
math
isinf
):
return
sys
hash_info
inf
if
else
sys
hash_info
inf
else
return
hash_fraction
as_integer_ratio
())
def
hash_complex
):
"""Compute the hash of a complex number z."""
hash_value
hash_float
real
sys
hash_info
imag
hash_float
imag
# do a signed reduction modulo 2**sys.hash_info.width
**
sys
hash_info
width
hash_value
hash_value
))
hash_value
if
hash_value
==
hash_value
return
hash_value
Boolean Type -
bool
Booleans represent truth values. The
bool
type has exactly two
constant instances:
True
and
False
The built-in function
bool()
converts any value to a boolean, if the
value can be interpreted as a truth value (see section
Truth Value Testing
above).
For logical operations, use the
boolean operators
and
or
and
not
When applying the bitwise operators
to two booleans, they
return a bool equivalent to the logical operations “and”, “or”, “xor”. However,
the logical operators
and
or
and
!=
should be preferred
over
and
Deprecated since version 3.12:
The use of the bitwise inversion operator
is deprecated and will
raise an error in Python 3.16.
bool
is a subclass of
int
(see
Numeric Types — int, float, complex
). In
many numeric contexts,
False
and
True
behave like the integers 0 and 1, respectively.
However, relying on this is discouraged; explicitly convert using
int()
instead.
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
and
in
statements. This method corresponds to the
tp_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
the
tp_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
generator
s 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,
and
are sequences of the same type,
and
are
integers and
is an arbitrary object that meets any type and value
restrictions imposed by
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.
Operation
Result
Notes
in
True
if an item of
is
equal to
, else
False
(1)
not
in
False
if an item of
is
equal to
, else
True
(1)
the concatenation of
and
(6)(7)
or
equivalent to adding
to
itself
times
(2)(7)
s[i]
th item of
, origin 0
(3)(8)
s[i:j]
slice of
from
to
(3)(4)
s[i:j:k]
slice of
from
to
with step
(3)(5)
len(s)
length of
min(s)
smallest item of
max(s)
largest item of
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
and
not
in
operations are used only for simple
containment testing in the general case, some specialised sequences
(such as
str
bytes
and
bytearray
) also use
them for subsequence testing:
>>>
"gg"
in
"eggs"
True
Values of
less than
are treated as
(which yields an empty
sequence of the same type as
). Note that items in the sequence
are not copied; they are referenced multiple times. This often haunts
new Python programmers; consider:
>>>
lists
[[]]
>>>
lists
[[], [], []]
>>>
lists
append
>>>
lists
[[3], [3], [3]]
What has happened is that
[[]]
is a one-element list containing an empty
list, so all three elements of
[[]]
are references to this single empty
list. Modifying any of the elements of
lists
modifies this single list.
You can create a list of different lists this way:
>>>
lists
[[]
for
in
range
)]
>>>
lists
append
>>>
lists
append
>>>
lists
append
>>>
lists
[[3], [5], [7]]
Further explanation is available in the FAQ entry
How do I create a multidimensional list?
If
or
is negative, the index is relative to the end of sequence
len(s)
or
len(s)
is substituted. But note that
-0
is
still
The slice of
from
to
is defined as the sequence of items with
index
such that
<=
If
is omitted or
None
, use
If
is omitted or
None
, use
len(s)
If
or
is less than
-len(s)
, use
If
or
is greater than
len(s)
, use
len(s)
If
is greater than or equal to
, the slice is empty.
The slice of
from
to
with step
is defined as the sequence of
items with index
n*k
such that
<=
(j-i)/k
. In other words,
the indices are
i+k
i+2*k
i+3*k
and so on, stopping when
is reached (but never including
). When
is positive,
and
are reduced to
len(s)
if they are greater.
When
is negative,
and
are reduced to
len(s)
if
they are greater. If
or
are omitted or
None
, they become
“end” values (which end depends on the sign of
). Note,
cannot be zero.
If
is
None
, it is treated like
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 use
str.join()
at the end or else write to an
io.StringIO
instance and retrieve its value when complete
if concatenating
bytes
objects, you can similarly use
bytes.join()
or
io.BytesIO
, or you can do in-place
concatenation with a
bytearray
object.
bytearray
objects are mutable and have an efficient overallocation mechanism
if concatenating
tuple
objects, extend a
list
instead
for 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.
An
IndexError
is raised if
is outside the sequence range.
Sequence Methods
Sequence types also support the following methods:
sequence.
count
value
Return the total number of occurrences of
value
in
sequence
sequence.
index
value
start
stop
Return the index of the first occurrence of
value
in
sequence
Raises
ValueError
if
value
is not found in
sequence
The
start
or
stop
arguments allow for efficient searching
of subsections of the sequence, beginning at
start
and ending at
stop
This is roughly equivalent to
start
sequence[start:stop].index(value)
only without copying any data.
Caution
Not all sequence types support passing the
start
and
stop
arguments.
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
is an instance of a mutable sequence type,
is any
iterable object and
is an arbitrary object that meets any type
and value restrictions imposed by
(for example,
bytearray
only
accepts integers that meet the value restriction
<=
<=
255
).
Operation
Result
Notes
s[i]
item
of
is replaced by
del
s[i]
removes item
of
s[i:j]
slice of
from
to
is replaced by the contents of
the iterable
del
s[i:j]
removes the elements of
s[i:j]
from the list
(same as
s[i:j]
[]
s[i:j:k]
the elements of
s[i:j:k]
are replaced by those of
(1)
del
s[i:j:k]
removes the elements of
s[i:j:k]
from the list
+=
extends
with the
contents of
(for the
most part the same as
s[len(s):len(s)]
*=
updates
with its contents
repeated
times
(2)
Notes:
If
is not equal to
must have the same length as the slice it is replacing.
The value
is an integer, or an object implementing
__index__()
. Zero and negative values of
clear
the sequence. Items in the sequence are not copied; they are referenced
multiple times, as explained for
under
Common Sequence Operations
Mutable Sequence Methods
Mutable sequence types also support the following methods:
sequence.
append
value
Append
value
to the end of the sequence.
This is equivalent to writing
seq[len(seq):len(seq)]
[value]
sequence.
clear
Added in version 3.3.
Remove all items from
sequence
This is equivalent to writing
del
sequence[:]
sequence.
copy
Added in version 3.3.
Create a shallow copy of
sequence
This is equivalent to writing
sequence[:]
Hint
The
copy()
method is not part of the
MutableSequence
ABC
but most concrete mutable sequence types provide it.
sequence.
extend
iterable
Extend
sequence
with the contents of
iterable
For the most part, this is the same as writing
seq[len(seq):len(seq)]
iterable
sequence.
insert
index
value
Insert
value
into
sequence
at the given
index
This is equivalent to writing
sequence[index:index]
[value]
sequence.
pop
index
-1
Retrieve the item at
index
and also removes it from
sequence
By default, the last item in
sequence
is removed and returned.
sequence.
remove
value
Remove the first item from
sequence
where
sequence[i]
==
value
Raises
ValueError
if
value
is not found in
sequence
sequence.
reverse
Reverse the items of
sequence
in place.
This method maintains economy of space when reversing a large sequence.
To remind users that it operates by side-effect, it returns
None
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
in
iterable]
Using the type constructor:
list()
or
list(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']
and
list(
(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 of
None
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 Techniques
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.
See also
For detailed information on thread-safety guarantees for
list
objects, see
Thread safety for list objects
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,
or
(a,
b,
c)
Using the
tuple()
built-in:
tuple()
or
tuple(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')
and
tuple(
[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, while
f((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 to
If the
start
argument is omitted, it defaults to
If
step
is zero,
ValueError
is raised.
For a positive
step
, the contents of a range
are determined by the
formula
r[i]
start
step*i
where
>=
and
r[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 are
>=
and
r[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 as
len()
) may raise
OverflowError
Range examples:
>>>
list
range
10
))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>>
list
range
11
))
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>>
list
range
30
))
[0, 5, 10, 15, 20, 25]
>>>
list
range
10
))
[0, 3, 6, 9]
>>>
list
range
10
))
[0, -1, -2, -3, -4, -5, -6, -7, -8, -9]
>>>
list
range
))
[]
>>>
list
range
))
[]
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
if the parameter was
not supplied)
stop
The value of the
stop
parameter
step
The value of the
step
parameter (or
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
):
>>>
range
20
>>>
range(0, 20, 2)
>>>
11
in
False
>>>
10
in
True
>>>
index
10
>>>
10
>>>
[:
range(0, 10, 2)
>>>
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).
Added the
start
stop
and
step
attributes.
See also
The
linspace recipe
shows how to implement a lazy version of range suitable for floating-point
applications.
Text and Binary Sequence Type Methods Summary
The following table summarizes the text and binary sequence types methods by
category.
Category
str
methods
bytes
and
bytearray
methods
Formatting
str.format()
str.format_map()
f-strings
printf-style String Formatting
printf-style Bytes Formatting
Searching and Replacing
str.find()
str.rfind()
bytes.find()
bytes.rfind()
str.index()
str.rindex()
bytes.index()
bytes.rindex()
str.startswith()
bytes.startswith()
str.endswith()
bytes.endswith()
str.count()
bytes.count()
str.replace()
bytes.replace()
Splitting and Joining
str.split()
str.rsplit()
bytes.split()
bytes.rsplit()
str.splitlines()
bytes.splitlines()
str.partition()
bytes.partition()
str.rpartition()
bytes.rpartition()
str.join()
bytes.join()
String Classification
str.isalpha()
bytes.isalpha()
str.isdecimal()
str.isdigit()
bytes.isdigit()
str.isnumeric()
str.isalnum()
bytes.isalnum()
str.isidentifier()
str.islower()
bytes.islower()
str.isupper()
bytes.isupper()
str.istitle()
bytes.istitle()
str.isspace()
bytes.isspace()
str.isprintable()
Case Manipulation
str.lower()
bytes.lower()
str.upper()
bytes.upper()
str.casefold()
str.capitalize()
bytes.capitalize()
str.title()
bytes.title()
str.swapcase()
bytes.swapcase()
Padding and Stripping
str.ljust()
str.rjust()
bytes.ljust()
bytes.rjust()
str.center()
bytes.center()
str.expandtabs()
bytes.expandtabs()
str.strip()
bytes.strip()
str.lstrip()
str.rstrip()
bytes.lstrip()
bytes.rstrip()
Translation and Encoding
str.translate()
bytes.translate()
str.maketrans()
bytes.maketrans()
str.encode()
bytes.decode()
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
(“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[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
prefix is
once again permitted on string literals. It has no effect on the meaning
of string literals and cannot be combined with the
prefix.
class
str
encoding
'utf-8'
errors
'strict'
class
str
object
class
str
object
encoding
errors
'strict'
class
str
object
errors
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)
returns
type(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, then
str()
falls back to returning
repr(object)
If at least one of
encoding
or
errors
is given,
object
should be a
bytes-like object
(e.g.
bytes
or
bytearray
). In
this case, if
object
is a
bytes
(or
bytearray
) object,
then
str(bytes,
encoding,
errors)
is equivalent to
bytes.decode(encoding,
errors)
. Otherwise, the bytes
object underlying the buffer object is obtained before calling
bytes.decode()
. See
Binary Sequence Types — bytes, bytearray, memoryview
and
Buffer Protocol
for information on buffer objects.
Passing a
bytes
object to
str()
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
'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
f-strings
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"
For example:
>>>
'straße'
lower
()
'straße'
>>>
'straße'
casefold
()
'strasse'
The casefolding algorithm is
described in section 3.13 ‘Default Case Folding’ of the Unicode Standard
Added 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)
. For example:
>>>
'Python'
center
10
' Python '
>>>
'Python'
center
10
'-'
'--Python--'
>>>
'Python'
center
'Python'
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.
If
sub
is empty, returns the number of empty strings between characters
which is the length of the string plus one. For example:
>>>
'spam, spam, spam'
count
'spam'
>>>
'spam, spam, spam'
count
'spam'
>>>
'spam, spam, spam'
count
'spam'
10
>>>
'spam, spam, spam'
count
'eggs'
>>>
'spam, spam, spam'
count
''
17
str.
encode
encoding
'utf-8'
errors
'strict'
Return the string encoded to
bytes
encoding
defaults to
'utf-8'
see
Standard Encodings
for possible values.
errors
controls how encoding errors are handled.
If
'strict'
(the default), a
UnicodeError
exception is raised.
Other possible values are
'ignore'
'replace'
'xmlcharrefreplace'
'backslashreplace'
and any
other name registered via
codecs.register_error()
See
Error Handlers
for details.
For performance reasons, the value of
errors
is not checked for validity
unless an encoding error actually occurs,
Python Development Mode
is enabled
or a
debug build
is used.
For example:
>>>
encoded_str_to_bytes
'Python'
encode
()
>>>
type
encoded_str_to_bytes

>>>
encoded_str_to_bytes
b'Python'
Changed in version 3.1:
Added support for keyword arguments.
Changed in version 3.9:
The value of the
errors
argument is now checked in
Python Development Mode
and
in
debug mode
str.
endswith
suffix
start
end
Return
True
if the string ends with the specified
suffix
, otherwise return
False
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. Using
start
and
end
is equivalent to
str[start:end].endswith(suffix)
. For example:
>>>
'Python'
endswith
'on'
True
>>>
'a tuple of suffixes'
endswith
((
'at'
'in'
))
False
>>>
'a tuple of suffixes'
endswith
((
'at'
'es'
))
True
>>>
'Python is amazing'
endswith
'is'
True
See also
startswith()
and
removesuffix()
str.
expandtabs
tabsize
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. For example:
>>>
'01
\t
012
\t
0123
\t
01234'
expandtabs
()
'01 012 0123 01234'
>>>
'01
\t
012
\t
0123
\t
01234'
expandtabs
'01 012 0123 01234'
>>>
'01
\t
012
\n
0123
\t
01234'
expandtabs
))
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.
For example:
>>>
'spam, spam, spam'
find
'sp'
>>>
'spam, spam, spam'
find
'sp'
See also
rfind()
and
index()
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 the
in
operator:
>>>
'Py'
in
'Python'
True
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. For example:
>>>
"The sum of 1 + 2 is
{0}
format
'The sum of 1 + 2 is 3'
>>>
"The sum of
{a}
{b}
is
{answer}
format
answer
'The sum of 1 + 2 is 3'
>>>
{1}
expects the
{0}
Inquisition!"
format
"Spanish"
"Nobody"
'Nobody expects the Spanish Inquisition!'
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 the
type
(ex:
'{:n}'.format(1234)
), the function temporarily sets the
LC_CTYPE
locale to the
LC_NUMERIC
locale to decode
decimal_point
and
thousands_sep
fields of
localeconv()
if
they are non-ASCII or longer than 1 byte, and the
LC_NUMERIC
locale is
different than the
LC_CTYPE
locale. This temporary change affects
other threads.
Changed in version 3.7:
When formatting a number with the
type, the function sets
temporarily the
LC_CTYPE
locale to the
LC_NUMERIC
locale in some
cases.
str.
format_map
mapping
Similar to
str.format(**mapping)
, except that
mapping
is
used directly and not copied to a
dict
. This is useful
if for example
mapping
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'
Added in version 3.2.
str.
index
sub
start
end
Like
find()
, but raise
ValueError
when the substring is
not found. For example:
>>>
'spam, spam, spam'
index
'spam'
>>>
'spam, spam, spam'
index
'eggs'
Traceback (most recent call last):
File
""
, line
, in

'spam, spam, spam'
index
'eggs'
~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^
ValueError
substring not found
See also
rindex()
str.
isalnum
Return
True
if all characters in the string are alphanumeric and there is at
least one character,
False
otherwise. A character
is alphanumeric if one
of the following returns
True
c.isalpha()
c.isdecimal()
c.isdigit()
, or
c.isnumeric()
. For example:
>>>
'abc123'
isalnum
()
True
>>>
'abc123!@#'
isalnum
()
False
>>>
''
isalnum
()
False
>>>
' '
isalnum
()
False
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 section 4.10 ‘Letters, Alphabetic, and
Ideographic’ of the Unicode Standard
For example:
>>>
'Letters and spaces'
isalpha
()
False
>>>
'LettersOnly'
isalpha
()
True
>>>
'µ'
isalpha
()
# non-ASCII characters can be considered alphabetical too
True
See
Unicode Properties
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. For example:
>>>
'ASCII characters'
isascii
()
True
>>>
'µ'
isascii
()
False
Added 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, such as U+0660, ARABIC-INDIC DIGIT
ZERO. Formally a decimal character is a character in the Unicode
General Category “Nd”. For example:
>>>
'0123456789'
isdecimal
()
True
>>>
'٠١٢٣٤٥٦٧٨٩'
isdecimal
()
# Arabic-Indic digits zero to nine
True
>>>
'alphabetic'
isdecimal
()
False
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
Names (identifiers and keywords)
keyword.iskeyword()
can be used to test whether string
is a reserved
identifier, such as
def
and
class
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
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.
For example:
>>>
'0123456789'
isnumeric
()
True
>>>
'٠١٢٣٤٥٦٧٨٩'
isnumeric
()
# Arabic-indic digit zero to nine
True
>>>
'⅕'
isnumeric
()
# Vulgar fraction one fifth
True
>>>
'²'
isdecimal
(),
'²'
isdigit
(),
'²'
isnumeric
()
(False, True, True)
See also
isdecimal()
and
isdigit()
. Numeric characters are
a superset of decimal numbers.
str.
isprintable
Return
True
if all characters in the string are printable,
False
if it
contains at least one non-printable character.
Here “printable” means the character is suitable for
repr()
to use in
its output; “non-printable” means that
repr()
on built-in types will
hex-escape the character. It has no bearing on the handling of strings
written to
sys.stdout
or
sys.stderr
The printable characters are those which in the Unicode character database
(see
unicodedata
) have a general category in group Letter, Mark,
Number, Punctuation, or Symbol (L, M, N, P, or S); plus the ASCII space 0x20.
Nonprintable characters are those in group Separator or Other (Z or C),
except the ASCII space.
For example:
>>>
''
isprintable
(),
' '
isprintable
()
(True, True)
>>>
\t
isprintable
(),
\n
isprintable
()
(False, False)
See also
isspace()
str.
isspace
Return
True
if there are only whitespace characters in the string and there is
at least one character,
False
otherwise.
For example:
>>>
''
isspace
()
False
>>>
' '
isspace
()
True
>>>
\t\n
isspace
()
# TAB and BREAK LINE
True
>>>
\u3000
isspace
()
# IDEOGRAPHIC SPACE
True
A character is
whitespace
if in the Unicode character database
(see
unicodedata
), either its general category is
Zs
(“Separator, space”), or its bidirectional class is one of
WS
, or
See also
isprintable()
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. Return
False
otherwise.
For example:
>>>
'Spam, Spam, Spam'
istitle
()
True
>>>
'spam, spam, spam'
istitle
()
False
>>>
'SPAM, SPAM, SPAM'
istitle
()
False
See also
title()
str.
isupper
Return
True
if all cased characters
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
TypeError
will be raised if there are any non-string values in
iterable
, including
bytes
objects. The separator between
elements is the string providing this method. For example:
>>>
', '
join
([
'spam'
'spam'
'spam'
])
'spam, spam, spam'
>>>
'-'
join
'Python'
'P-y-t-h-o-n'
See also
split()
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)
For example:
>>>
'Python'
ljust
10
'Python '
>>>
'Python'
ljust
10
'.'
'Python....'
>>>
'Monty Python'
ljust
10
'.'
'Monty Python'
See also
rjust()
str.
lower
Return a copy of the string with all the cased characters
converted to
lowercase. For example:
>>>
'Lower Method Example'
lower
()
'lower method example'
The lowercasing algorithm used is
described in section 3.13 ‘Default Case Folding’ of the Unicode Standard
str.
lstrip
chars
None
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
dict
static
str.
maketrans
from
to
remove=''
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
from
will be mapped to the character at
the same position in
to
. 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.
For example:
>>>
'Monty Python'
partition
' '
('Monty', ' ', 'Python')
>>>
"Monty Python's Flying Circus"
partition
' '
('Monty', ' ', "Python's Flying Circus")
>>>
'Monty Python'
partition
'-'
('Monty Python', '', '')
See also
rpartition()
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'
Added in version 3.9.
See also
removesuffix()
and
startswith()
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'
Added in version 3.9.
See also
removeprefix()
and
endswith()
str.
replace
old
new
count
-1
Return a copy of the string with all occurrences of substring
old
replaced by
new
. If
count
is given, only the first
count
occurrences are replaced.
If
count
is not specified or
-1
, then all occurrences are replaced.
For example:
>>>
'spam, spam, spam'
replace
'spam'
'eggs'
'eggs, eggs, eggs'
>>>
'spam, spam, spam'
replace
'spam'
'eggs'
'eggs, spam, spam'
Changed in version 3.13:
count
is now supported as a keyword argument.
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.
For example:
>>>
'spam, spam, spam'
rfind
'sp'
12
>>>
'spam, spam, spam'
rfind
'sp'
10
See also
find()
and
rindex()
str.
rindex
sub
start
end
Like
rfind()
but raises
ValueError
when the substring
sub
is not
found.
For example:
>>>
'spam, spam, spam'
rindex
'spam'
12
>>>
'spam, spam, spam'
rindex
'eggs'
Traceback (most recent call last):
File
""
, line
, in

'spam, spam, spam'
rindex
'eggs'
~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^
ValueError
substring not found
See also
index()
and
find()
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)
For example:
>>>
'Python'
rjust
10
' Python'
>>>
'Python'
rjust
10
'.'
'....Python'
>>>
'Monty Python'
rjust
10
'.'
'Monty Python'
See also
ljust()
and
zfill()
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.
For example:
>>>
'Monty Python'
rpartition
' '
('Monty', ' ', 'Python')
>>>
"Monty Python's Flying Circus"
rpartition
' '
("Monty Python's Flying", ' ', 'Circus')
>>>
'Monty Python'
rpartition
'-'
('', '', 'Monty Python')
See also
partition()
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 like
split()
which is described in detail below.
str.
rstrip
chars
None
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.
For example:
>>>
' spacious '
rstrip
()
' spacious'
>>>
'mississippi'
rstrip
'ipz'
'mississ'
See
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'
See also
strip()
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
as a single delimiter (to split with multiple delimiters, use
re.split()
). Splitting an empty string with a specified separator
returns
['']
For example:
>>>
'1,2,3'
split
','
['1', '2', '3']
>>>
'1,2,3'
split
','
maxsplit
['1', '2,3']
>>>
'1,2,,3,'
split
','
['1', '2', '', '3', '']
>>>
'1<>2<>3<4'
split
'<>'
['1', '2', '3<4']
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 a
None
separator
returns
[]
For example:
>>>
'1 2 3'
split
()
['1', '2', '3']
>>>
'1 2 3'
split
maxsplit
['1', '2 3']
>>>
' 1 2 3 '
split
()
['1', '2', '3']
If
sep
is not specified or is
None
and
maxsplit
is
, only
leading runs of consecutive whitespace are considered.
For example:
>>>
""
split
None
[]
>>>
" "
split
None
[]
>>>
" foo "
split
maxsplit
['foo ']
See also
join()
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\n
de fg
\r
kl
\r\n
splitlines
()
['ab c', '', 'de fg', 'kl']
>>>
'ab c
\n\n
de fg
\r
kl
\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 return
False
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.
For example:
>>>
'Python'
startswith
'Py'
True
>>>
'a tuple of prefixes'
startswith
((
'at'
'a'
))
True
>>>
'Python is amazing'
startswith
'is'
True
See also
endswith()
and
removeprefix()
str.
strip
chars
None
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.
For example:
>>>
' 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'
See also
rstrip()
str.
swapcase
Return a copy of the string with uppercase characters converted to lowercase and
vice versa. For example:
>>>
'Hello World'
swapcase
()
'hELLO wORLD'
Note that it is not necessarily true that
s.swapcase().swapcase()
==
For example:
>>>
'straße'
swapcase
()
swapcase
()
'strasse'
See also
str.lower()
and
str.upper()
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
):
...
return
re
sub
"[A-Za-z]+('[A-Za-z]+)?"
...
lambda
mo
mo
group
capitalize
(),
...
...
>>>
titlecase
"they're bill's friends."
"They're Bill's Friends."
See also
istitle()
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; return
None
, to delete the character from the return string; or raise a
LookupError
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
converted to
uppercase. Note that
s.upper().isupper()
might be
False
if
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 ‘Default Case Folding’ 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 to
len(s)
For example:
>>>
"42"
zfill
'00042'
>>>
"-42"
zfill
'-0042'
See also
rjust()
Formatted String Literals (f-strings)
Added in version 3.6.
Changed in version 3.7:
The
await
and
async
for
can be used in expressions
within f-strings.
Changed in version 3.8:
Added the debug specifier (
Changed in version 3.12:
Many restrictions on expressions within f-strings have been removed.
Notably, nested strings, comments, and backslashes are now permitted.
An
f-string
(formally a
formatted string literal
) is
a string literal that is prefixed with
or
This type of string literal allows embedding the results of arbitrary Python
expressions within
replacement fields
, which are delimited by curly
brackets (
{}
).
Each replacement field must contain an expression, optionally followed by:
debug specifier
– an equal sign (
);
conversion specifier
!s
!r
or
!a
; and/or
format specifier
prefixed with a colon (
).
See the
Lexical Analysis section on f-strings
for details
on the syntax of these fields.
Debug specifier
Added in version 3.8.
If a debug specifier – an equal sign (
) – appears after the replacement
field expression, the resulting f-string will contain the expression’s source,
the equal sign, and the value of the expression.
This is often useful for debugging:
>>>
number
14.3
>>>
number
=}
'number=14.3'
Whitespace before, inside and after the expression, as well as whitespace
after the equal sign, is significant — it is retained in the result:
>>>
number
= }
' number - 4 = 10.3'
Conversion specifier
By default, the value of a replacement field expression is converted to
a string using
str()
>>>
from
fractions
import
Fraction
>>>
one_third
Fraction
>>>
one_third
'1/3'
When a debug specifier but no format specifier is used, the default conversion
instead uses
repr()
>>>
one_third
= }
'one_third = Fraction(1, 3)'
The conversion can be specified explicitly using one of these specifiers:
!s
for
str()
!r
for
repr()
!a
for
ascii()
For example:
>>>
str
one_third
'1/3'
>>>
repr
one_third
'Fraction(1, 3)'
>>>
one_third
!s}
is
one_third
!r}
'1/3 is Fraction(1, 3)'
>>>
string
"¡kočka 😸!"
>>>
ascii
string
"'\\xa1ko\\u010dka \\U0001f638!'"
>>>
string
= !a}
"string = '\\xa1ko\\u010dka \\U0001f638!'"
Format specifier
After the expression has been evaluated, and possibly converted using an
explicit conversion specifier, it is formatted using the
format()
function.
If the replacement field includes a
format specifier
introduced by a colon
), the specifier is passed to
format()
as the second argument.
The result of
format()
is then used as the final value for the
replacement field. For example:
>>>
from
fractions
import
Fraction
>>>
one_third
Fraction
>>>
one_third
.6f
'0.333333'
>>>
one_third
_^+10
'___+1/3___'
>>>
>>>
one_third
!r:
_^20
'___Fraction(1, 3)___'
>>>
one_third
= :
~>10
~'
'one_third = ~~~~~~~1/3~'
Template String Literals (t-strings)
An
t-string
(formally a
template string literal
) is
a string literal that is prefixed with
or
These strings follow the same syntax and evaluation rules as
formatted string literals
with for the following differences:
Rather than evaluating to a
str
object, template string literals evaluate
to a
string.templatelib.Template
object.
The
format()
protocol is not used.
Instead, the format specifier and conversions (if any) are passed to
a new
Interpolation
object that is created
for each evaluated expression.
It is up to code that processes the resulting
Template
object to decide how to handle format specifiers and conversions.
Format specifiers containing nested replacement fields are evaluated eagerly,
prior to being passed to the
Interpolation
object.
For instance, an interpolation of the form
{amount:.{precision}f}
will
evaluate the inner expression
{precision}
to determine the value of the
format_spec
attribute.
If
precision
were to be
, the resulting format specifier
would be
'.2f'
When the equals sign
'='
is provided in an interpolation expression,
the text of the expression is appended to the literal string that precedes
the relevant interpolation.
This includes the equals sign and any surrounding whitespace.
The
Interpolation
instance for the expression will be created as
normal, except that
conversion
will
be set to ‘
’ (
repr()
) by default.
If an explicit conversion or format specifier are provided,
this will override the default behaviour.
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
formatted string literals
, the
str.format()
interface, or
string.Template
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()
function in the C language.
For example:
>>>
%s
has
%d
quote types.'
'Python'
))
Python has 2 quote types.
If
format
requires a single argument,
values
may be a single non-tuple
object.
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:
>>>
%(language)s
has
%(number)03d
quote types.'
...
'language'
"Python"
"number"
})
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).
'0'
The conversion will be zero padded for numeric values.
'-'
The converted value is left adjusted (overrides the
'0'
conversion if both are given).
(a space) A blank should be left before a positive number (or empty
string) produced by a signed conversion.
'+'
A sign character (
'+'
or
'-'
) will precede the conversion
(overrides a “space” flag).
A length modifier (
, or
) 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
'd'
Signed integer decimal.
'i'
Signed integer decimal.
'o'
Signed octal value.
(1)
'u'
Obsolete type – it is identical to
'd'
(6)
'x'
Signed hexadecimal (lowercase).
(2)
'X'
Signed hexadecimal (uppercase).
(2)
'e'
Floating-point exponential format (lowercase).
(3)
'E'
Floating-point exponential format (uppercase).
(3)
'f'
Floating-point decimal format.
(3)
'F'
Floating-point decimal format.
(3)
'g'
Floating-point format. Uses lowercase exponential
format if exponent is less than -4 or not less than
precision, decimal format otherwise.
(4)
'G'
Floating-point format. Uses uppercase exponential
format if exponent is less than -4 or not less than
precision, decimal format otherwise.
(4)
'c'
Single character (accepts integer or single
character string).
'r'
String (converts any Python object using
repr()
).
(5)
's'
String (converts any Python object using
str()
).
(5)
'a'
String (converts any Python object using
ascii()
).
(5)
'%'
No argument is converted, results in a
'%'
character in the result.
For floating-point formats, the result should be correctly rounded to a given
precision
of digits after the decimal point. The rounding mode matches
that of the
round()
builtin.
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
, the output is truncated to
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
b''
class
bytes
source
encoding
errors
'strict'
Firstly, the syntax for bytes literals is largely the same as that for string
literals, except that a
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
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
<=
256
(attempts to
violate this restriction will trigger
ValueError
). 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.
Changed in version 3.14:
bytes.fromhex()
now accepts ASCII
bytes
and
bytes-like objects
as input.
A reverse conversion function exists to transform a bytes object into its
hexadecimal representation.
hex
bytes_per_sep
hex
sep
bytes_per_sep
Return a string object containing two hexadecimal digits for each
byte in the instance.
>>>
\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, this separator will be included 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
\xf0\xf1\xf2
>>>
value
hex
'-'
'f0-f1-f2'
>>>
value
hex
'_'
'f0_f1f2'
>>>
'UUDDLRLRAB'
hex
' '
'55554444 4c524c52 4142'
Added 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[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)
Bytearray Objects
bytearray
objects are a mutable counterpart to
bytes
objects.
class
bytearray
source
b''
class
bytearray
source
encoding
errors
'strict'
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.
Changed in version 3.14:
bytearray.fromhex()
now accepts ASCII
bytes
and
bytes-like objects
as input.
A reverse conversion function exists to transform a bytearray object into its
hexadecimal representation.
hex
bytes_per_sep
hex
sep
bytes_per_sep
Return a string object containing two hexadecimal digits for each
byte in the instance.
>>>
bytearray
\xf0\xf1\xf2
hex
()
'f0f1f2'
Added 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.
resize
size
Resize the
bytearray
to contain
size
bytes.
size
must be
greater than or equal to 0.
If the
bytearray
needs to shrink, bytes beyond
size
are truncated.
If the
bytearray
needs to grow, all new bytes, those beyond
size
will be set to null bytes.
This is equivalent to:
>>>
def
resize
ba
size
):
...
if
len
ba
size
...
del
ba
size
:]
...
else
...
ba
+=
\0
size
len
ba
))
Examples:
>>>
shrink
bytearray
'abc'
>>>
shrink
resize
>>>
shrink
len
shrink
))
(bytearray(b'a'), 1)
>>>
grow
bytearray
'abc'
>>>
grow
resize
>>>
grow
len
grow
))
(bytearray(b'abc\x00\x00'), 5)
Added in version 3.14.
Since bytearray objects are sequences of integers (akin to a list), for a
bytearray object
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)
See also
For detailed information on thread-safety guarantees for
bytearray
objects, see
Thread safety for bytearray objects
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:
"abc"
replace
"a"
"f"
and:
"abc"
replace
"a"
"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.
If
sub
is empty, returns the number of empty slices between characters
which is the length of the bytes object plus one.
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:
>>>
'TestHook'
removeprefix
'Test'
b'Hook'
>>>
'BaseTestCase'
removeprefix
'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.
Added 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:
>>>
'MiscTests'
removesuffix
'Tests'
b'Misc'
>>>
'TmpDirMixin'
removesuffix
'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.
Added in version 3.9.
bytes.
decode
encoding
'utf-8'
errors
'strict'
bytearray.
decode
encoding
'utf-8'
errors
'strict'
Return the bytes decoded to a
str
encoding
defaults to
'utf-8'
see
Standard Encodings
for possible values.
errors
controls how decoding errors are handled.
If
'strict'
(the default), a
UnicodeError
exception is raised.
Other possible values are
'ignore'
'replace'
and any other name registered via
codecs.register_error()
See
Error Handlers
for details.
For performance reasons, the value of
errors
is not checked for validity
unless a decoding error actually occurs,
Python Development Mode
is enabled or a
debug build
is used.
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 value of the
errors
argument is now checked in
Python 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 return
False
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 the
in
operator:
>>>
'Py'
in
'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 raise
ValueError
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
, including
str
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.
Added 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
-1
bytearray.
replace
old
new
count
-1
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 raises
ValueError
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 return
False
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:
>>>
'read this short text'
translate
None
'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
b'
bytearray.
center
width
fillbyte
b'
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 to
len(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
b'
bytearray.
ljust
width
fillbyte
b'
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 to
len(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
bytes
None
bytearray.
lstrip
bytes
None
Return a copy of the sequence with specified leading bytes removed. The
bytes
argument is a binary sequence specifying the set of byte values to
be removed. If omitted or
None
, the
bytes
argument defaults
to removing ASCII whitespace. The
bytes
argument is not a prefix;
rather, all combinations of its values are stripped:
>>>
' spacious '
lstrip
()
b'spacious '
>>>
'www.example.com'
lstrip
'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:
>>>
'Arthur: three!'
lstrip
'Arthur: '
b'ee!'
>>>
'Arthur: three!'
removeprefix
'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
b'
bytearray.
rjust
width
fillbyte
b'
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 to
len(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 like
split()
which is described in detail below.
bytes.
rstrip
bytes
None
bytearray.
rstrip
bytes
None
Return a copy of the sequence with specified trailing bytes removed. The
bytes
argument is a binary sequence specifying the set of byte values to
be removed. If omitted or
None
, the
bytes
argument defaults to
removing ASCII whitespace. The
bytes
argument is not a suffix; rather,
all combinations of its values are stripped:
>>>
' spacious '
rstrip
()
b' spacious'
>>>
'mississippi'
rstrip
'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:
>>>
'Monty Python'
rstrip
' Python'
b'M'
>>>
'Monty Python'
removesuffix
' 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 as a single delimiter. 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:
>>>
'1,2,3'
split
','
[b'1', b'2', b'3']
>>>
'1,2,3'
split
','
maxsplit
[b'1', b'2,3']
>>>
'1,2,,3,'
split
','
[b'1', b'2', b'', b'3', b'']
>>>
'1<>2<>3<4'
split
'<>'
[b'1', b'2', b'3<4']
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:
>>>
'1 2 3'
split
()
[b'1', b'2', b'3']
>>>
'1 2 3'
split
maxsplit
[b'1', b'2 3']
>>>
' 1 2 3 '
split
()
[b'1', b'2', b'3']
bytes.
strip
bytes
None
bytearray.
strip
bytes
None
Return a copy of the sequence with specified leading and trailing bytes
removed. The
bytes
argument is a binary sequence specifying the set of
byte values to be removed. If omitted or
None
, the
bytes
argument defaults to removing ASCII whitespace. The
bytes
argument is
not a prefix or suffix; rather, all combinations of its values are
stripped:
>>>
' spacious '
strip
()
b'spacious'
>>>
'www.example.com'
strip
'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
bytearray.
expandtabs
tabsize
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:
>>>
'01
\t
012
\t
0123
\t
01234'
expandtabs
()
b'01 012 0123 01234'
>>>
'01
\t
012
\t
0123
\t
01234'
expandtabs
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 sequence
b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
. ASCII decimal
digits are those byte values in the sequence
b'0123456789'
For example:
>>>
'ABCabc1'
isalnum
()
True
>>>
'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 sequence
b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
For example:
>>>
'ABCabc'
isalpha
()
True
>>>
'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.
Added 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 sequence
b'0123456789'
For example:
>>>
'1234'
isdigit
()
True
>>>
'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:
>>>
'hello world'
islower
()
True
>>>
'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 sequence
b'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 sequence
b'
\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. See
bytes.title()
for more details on the
definition of “titlecase”.
For example:
>>>
'Hello World'
istitle
()
True
>>>
'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:
>>>
'HELLO WORLD'
isupper
()
True
>>>
'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 sequence
b'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:
>>>
'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 sequence
b'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:
>>>
'ab c
\n\n
de fg
\r
kl
\r\n
splitlines
()
[b'ab c', b'', b'de fg', b'kl']
>>>
'ab c
\n\n
de fg
\r
kl
\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:
>>>
""
split
\n
),
"Two lines
\n
split
\n
([b''], [b'Two lines', b''])
>>>
""
splitlines
(),
"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:
>>>
'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 sequence
b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
Unlike
str.swapcase()
, it is always the case that
bin.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:
>>>
'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 sequence
b'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:
>>>
"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
):
...
return
re
sub
rb
"[A-Za-z]+('[A-Za-z]+)?"
...
lambda
mo
mo
group
)[
upper
()
...
mo
group
)[
:]
lower
(),
...
...
>>>
titlecase
"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:
>>>
'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 sequence
b'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. For
bytes
objects, the original sequence is
returned if
width
is less than or equal to
len(seq)
For example:
>>>
"42"
zfill
b'00042'
>>>
"-42"
zfill
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.
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:
>>>
%(language)s
has
%(number)03d
quote types.'
...
'language'
"Python"
"number"
})
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).
'0'
The conversion will be zero padded for numeric values.
'-'
The converted value is left adjusted (overrides the
'0'
conversion if both are given).
(a space) A blank should be left before a positive number (or empty
string) produced by a signed conversion.
'+'
A sign character (
'+'
or
'-'
) will precede the conversion
(overrides a “space” flag).
A length modifier (
, or
) 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
'd'
Signed integer decimal.
'i'
Signed integer decimal.
'o'
Signed octal value.
(1)
'u'
Obsolete type – it is identical to
'd'
(8)
'x'
Signed hexadecimal (lowercase).
(2)
'X'
Signed hexadecimal (uppercase).
(2)
'e'
Floating-point exponential format (lowercase).
(3)
'E'
Floating-point exponential format (uppercase).
(3)
'f'
Floating-point decimal format.
(3)
'F'
Floating-point decimal format.
(3)
'g'
Floating-point format. Uses lowercase exponential
format if exponent is less than -4 or not less than
precision, decimal format otherwise.
(4)
'G'
Floating-point format. Uses uppercase exponential
format if exponent is less than -4 or not less than
precision, decimal format otherwise.
(4)
'c'
Single byte (accepts integer or single
byte objects).
'b'
Bytes (any object that follows the
buffer protocol
or has
__bytes__()
).
(5)
's'
's'
is an alias for
'b'
and should only
be used for Python2/3 code bases.
(6)
'a'
Bytes (converts any Python object using
repr(obj).encode('ascii',
'backslashreplace')
).
(5)
'r'
'r'
is an alias for
'a'
and should only
be used for Python2/3 code bases.
(7)
'%'
No argument is converted, results in a
'%'
character in the result.
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
, the output is truncated to
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
Added 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 include
bytes
and
bytearray
memoryview
has the notion of an
element
, which is the
atomic memory unit handled by the originating
object
. For many simple
types such as
bytes
and
bytearray
, an element is a single
byte, but other types such as
array.array
may have bigger elements.
len(view)
is equal to the length of
tolist
, which
is the nested list representation of the view. If
view.ndim
this is equal to the number of elements in the view.
Changed in version 3.12:
If
view.ndim
==
len(view)
now raises
TypeError
instead of returning 1.
The
itemsize
attribute will give you the number of
bytes in a single element.
memoryview
supports slicing and indexing to expose its data.
One-dimensional slicing will result in a subview:
>>>
memoryview
'abcefg'
>>>
98
>>>
103
>>>

>>>
bytes
])
b'bce'
If
format
is one of the native format specifiers
from the
struct
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
>>>
array
array
'l'
11111111
22222222
33333333
44444444
])
>>>
memoryview
>>>
-11111111
>>>
44444444
>>>
[::
tolist
()
[-11111111, -33333333]
If the underlying object is writable, the memoryview supports
one-dimensional slice assignment. Resizing is not allowed:
>>>
data
bytearray
'abcefg'
>>>
memoryview
data
>>>
readonly
False
>>>
ord
'z'
>>>
data
bytearray(b'zbcefg')
>>>
'123'
>>>
data
bytearray(b'z123fg')
>>>
'spam'
Traceback (most recent call last):
File
""
, line
, in

ValueError
memoryview assignment: lvalue and rvalue have different structures
>>>
'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())
>>>
memoryview
'abcefg'
>>>
hash
==
hash
'abcefg'
True
>>>
hash
])
==
hash
'ce'
True
>>>
hash
[::
])
==
hash
'abcefg'
[::
])
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.
Changed in version 3.14:
memoryview is now a
generic type
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 by
tolist()
and
are equal if
v.tolist()
==
w.tolist()
>>>
import
array
>>>
array
array
'I'
])
>>>
array
array
'd'
1.0
2.0
3.0
4.0
5.0
])
>>>
array
array
'b'
])
>>>
memoryview
>>>
memoryview
>>>
==
==
==
True
>>>
tolist
()
==
tolist
()
==
tolist
()
==
tolist
()
True
>>>
[::
>>>
==
True
>>>
tolist
()
==
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
>>>
memoryview
point
>>>
memoryview
point
>>>
==
point
False
>>>
==
False
Note that, as with floating-point numbers,
is
does
not
imply
==
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
'C'
Return the data in the buffer as a bytestring. This is equivalent to
calling the
bytes
constructor on the memoryview.
>>>
memoryview
"abc"
>>>
tobytes
()
b'abc'
>>>
bytes
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 in
struct
module syntax.
Added 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
bytes_per_sep
hex
sep
bytes_per_sep
Return a string object containing two hexadecimal digits for each
byte in the buffer.
>>>
memoryview
"abc"
>>>
hex
()
'616263'
Added 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
'abc'
tolist
()
[97, 98, 99]
>>>
import
array
>>>
array
array
'd'
1.1
2.2
3.3
])
>>>
memoryview
>>>
tolist
()
[1.1, 2.2, 3.3]
Changed in version 3.3:
tolist()
now supports all single character native formats in
struct
module syntax as well as multi-dimensional
representations.
toreadonly
Return a readonly version of the memoryview object. The original
memoryview object is unchanged.
>>>
memoryview
bytearray
'abc'
))
>>>
mm
toreadonly
()
>>>
mm
tolist
()
[97, 98, 99]
>>>
mm
42
Traceback (most recent call last):
File
""
, line
, in

TypeError
cannot modify read-only memory
>>>
43
>>>
mm
tolist
()
[43, 98, 99]
Added 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,
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
(except
release()
itself which can
be called multiple times):
>>>
memoryview
'abc'
>>>
release
()
>>>
Traceback (most recent call last):
File
""
, line
, 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
'abc'
as
...
...
97
>>>
Traceback (most recent call last):
File
""
, line
, in

ValueError
operation forbidden on released memoryview object
Added in version 3.2.
cast
format
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.
Note that all byte lengths may depend on the operating system.
Cast 1D/long to 1D/unsigned bytes:
>>>
import
array
>>>
array
array
'l'
])
>>>
memoryview
>>>
format
'l'
>>>
itemsize
>>>
len
>>>
nbytes
24
>>>
cast
'B'
>>>
format
'B'
>>>
itemsize
>>>
len
24
>>>
nbytes
24
Cast 1D/unsigned bytes to 1D/char:
>>>
bytearray
'zyz'
>>>
memoryview
>>>
'a'
Traceback (most recent call last):
...
TypeError
memoryview: invalid type for format 'B'
>>>
cast
'c'
>>>
'a'
>>>
bytearray(b'ayz')
Cast 1D/bytes to 3D/ints to 1D/signed char:
>>>
import
struct
>>>
buf
struct
pack
"i"
12
list
range
12
)))
>>>
memoryview
buf
>>>
cast
'i'
shape
])
>>>
tolist
()
[[[0, 1, 2], [3, 4, 5]], [[6, 7, 8], [9, 10, 11]]]
>>>
format
'i'
>>>
itemsize
>>>
len
>>>
nbytes
48
>>>
cast
'b'
>>>
format
'b'
>>>
itemsize
>>>
len
48
>>>
nbytes
48
Cast 1D/unsigned long to 2D/unsigned long:
>>>
buf
struct
pack
"L"
list
range
)))
>>>
memoryview
buf
>>>
cast
'L'
shape
])
>>>
len
>>>
nbytes
48
>>>
tolist
()
[[0, 1, 2], [3, 4, 5]]
Added in version 3.3.
Changed in version 3.5:
The source format is no longer restricted when casting to a byte view.
count
value
Count the number of occurrences of
value
Added in version 3.14.
index
value
start
stop
sys.maxsize
Return the index of the first occurrence of
value
(at or after
index
start
and before index
stop
).
Raises a
ValueError
if
value
cannot be found.
Added in version 3.14.
There are also several readonly attributes available:
obj
The underlying object of the memoryview:
>>>
bytearray
'xyz'
>>>
memoryview
>>>
obj
is
True
Added 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 to
len(m)
>>>
import
array
>>>
array
array
'i'
])
>>>
memoryview
>>>
len
>>>
nbytes
20
>>>
[::
>>>
len
>>>
nbytes
12
>>>
len
tobytes
())
12
Multi-dimensional arrays:
>>>
import
struct
>>>
buf
struct
pack
"d"
12
1.5
for
in
range
12
)])
>>>
memoryview
buf
>>>
cast
'd'
shape
])
>>>
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
>>>
nbytes
96
Added 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 that
memoryview(b'abc')[0]
==
b'abc'[0]
==
97
itemsize
The size in bytes of each element of the memoryview:
>>>
import
array
struct
>>>
memoryview
array
array
'H'
32000
32001
32002
]))
>>>
itemsize
>>>
32000
>>>
struct
calcsize
'H'
==
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
Added in version 3.3.
f_contiguous
A bool indicating whether the memory is Fortran
contiguous
Added in version 3.3.
contiguous
A bool indicating whether the memory is
contiguous
Added in version 3.3.
For information on the thread safety of
memoryview
objects in
the
free-threaded build
, see
Thread safety for memoryview objects
Set Types —
set
frozenset
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
in
set
len(set)
, and
for
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
in
'abracadabra'
if
not
in
'abc'}
Use the type constructor:
set()
set('foobar')
set(['a',
'b',
'foo'])
Instances of
set
and
frozenset
provide the following
operations:
len(s)
Return the number of elements in set
(cardinality of
).
in
Test
for membership in
not
in
Test
for non-membership in
frozenset.
isdisjoint
other
set.
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.
frozenset.
issubset
other
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
frozenset.
issuperset
other
set.
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
frozenset.
union
others
set.
union
others
set
other
...
Return a new set with elements from the set and all others.
frozenset.
intersection
others
set.
intersection
others
set
other
...
Return a new set with elements common to the set and all others.
frozenset.
difference
others
set.
difference
others
set
other
...
Return a new set with elements in the set that are not in the others.
frozenset.
symmetric_difference
other
set.
symmetric_difference
other
set
other
Return a new set with elements in either the set or
other
but not both.
frozenset.
copy
set.
copy
Return a shallow copy of the set.
Note, the non-operator versions of
union()
intersection()
difference()
symmetric_difference()
issubset()
, and
issuperset()
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 like
set('abc')
'cbs'
in favor of the more readable
set('abc').intersection('cbs')
Both
set
and
frozenset
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 of
frozenset
based on their members. For example,
set('abc')
==
frozenset('abc')
returns
True
and so does
set('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
aa==b
, or
a>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 with
frozenset
return the type of the first operand. For example:
frozenset('ab')
set('bc')
returns an instance of
frozenset
The following table lists operations available for
set
that do not
apply to immutable instances of
frozenset
set.
update
others
set
|=
other
...
Update the set, adding elements from all others.
set.
intersection_update
others
set
&=
other
...
Update the set, keeping only elements found in it and all others.
set.
difference_update
others
set
-=
other
...
Update the set, removing elements found in others.
set.
symmetric_difference_update
other
set
^=
other
Update the set, keeping only elements found in either set, but not in both.
set.
add
elem
Add element
elem
to the set.
set.
remove
elem
Remove element
elem
from the set. Raises
KeyError
if
elem
is
not contained in the set.
set.
discard
elem
Remove element
elem
from the set if it is present.
set.
pop
Remove and return an arbitrary element from the set. Raises
KeyError
if the set is empty.
set.
clear
Remove all elements from the set.
Note, the non-operator versions of the
update()
intersection_update()
difference_update()
, and
symmetric_difference_update()
methods will accept any iterable as an
argument.
Note, the
elem
argument to the
__contains__()
remove()
, and
discard()
methods may be a set. To support searching for an equivalent
frozenset, a temporary one is created from
elem
See also
For detailed information on thread-safety guarantees for
set
objects, see
Thread safety for set objects
Mapping Types —
dict
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.
Values that compare equal (such as
1.0
, and
True
can be used interchangeably to index the same dictionary entry.
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:
**
for
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 defines a
keys()
method, a
dictionary is created by calling
__getitem__()
on the argument with
each returned key from the method. Otherwise, the positional argument must be an
iterable
object. Each item in the iterable must itself be an iterable
with exactly two elements. The first element of each item becomes a key in the
new dictionary, and the second element 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.
Dictionaries compare equal if and only if they have the same
(key,
value)
pairs (regardless of ordering). Order comparisons (‘<’, ‘<=’, ‘>=’, ‘>’) raise
TypeError
. To illustrate dictionary creation and equality,
the following examples all return a dictionary equal to
{"one":
1,
"two":
2,
"three":
3}
>>>
dict
one
two
three
>>>
'one'
'two'
'three'
>>>
dict
zip
([
'one'
'two'
'three'
],
]))
>>>
dict
([(
'two'
),
'one'
),
'three'
)])
>>>
dict
({
'three'
'one'
'two'
})
>>>
dict
({
'one'
'three'
},
two
>>>
==
==
==
==
==
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.
Dictionaries preserve insertion order. Note that updating a key does not
affect the order. Keys added after deletion are inserted at the end.
>>>
"one"
"two"
"three"
"four"
>>>
{'one': 1, 'two': 2, 'three': 3, 'four': 4}
>>>
list
['one', 'two', 'three', 'four']
>>>
list
values
())
[1, 2, 3, 4]
>>>
"one"
42
>>>
{'one': 42, 'two': 2, 'three': 3, 'four': 4}
>>>
del
"two"
>>>
"two"
None
>>>
{'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.
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
len(d)
Return the number of items in the dictionary
d[key]
Return the item of
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, the
d[key]
operation calls that method with the key
key
as argument. The
d[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
...
>>>
Counter
()
>>>
'red'
>>>
'red'
+=
>>>
'red'
The example above shows part of the implementation of
collections.Counter
A different
__missing__()
method is used
by
collections.defaultdict
d[key]
value
Set
d[key]
to
value
del
d[key]
Remove
d[key]
from
. Raises a
KeyError
if
key
is not in the
map.
key
in
Return
True
if
has a key
key
, else
False
key
not
in
Equivalent to
not
key
in
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
None
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 to
None
. 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
None
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 a
KeyError
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
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,
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, calling
popitem()
raises a
KeyError
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())
Added in version 3.8.
setdefault
key
default
None
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
**
kwargs
update
mapping
**
kwargs
update
iterable
**
kwargs
Update the dictionary with the key/value pairs from
mapping
or
iterable
and
kwargs
, overwriting
existing keys. Return
None
update()
accepts either another object with a
keys()
method (in
which case
__getitem__()
is called with every key returned from
the method) 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 return
False
. This also applies when comparing
dict.values()
to itself:
>>>
'a'
>>>
values
()
==
values
()
False
other
Create a new dictionary with the merged keys and values of
and
other
, which must both be dictionaries. The values of
other
take
priority when
and
other
share keys.
Added in version 3.9.
|=
other
Update the dictionary
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
and
other
share keys.
Added in version 3.9.
Dictionaries and dictionary views are reversible.
>>>
"one"
"two"
"three"
"four"
>>>
{'one': 1, 'two': 2, 'three': 3, 'four': 4}
>>>
list
reversed
))
['four', 'three', 'two', 'one']
>>>
list
reversed
values
()))
[4, 3, 2, 1]
>>>
list
reversed
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
See also
For detailed information on thread-safety guarantees for
dict
objects, see
Thread safety for dict objects
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
using
zip()
pairs
zip(d.values(),
d.keys())
. Another way to
create the same list is
pairs
[(v,
k)
for
(k,
v)
in
d.items()]
Iterating views while adding or deleting entries in the dictionary may raise
RuntimeError
or fail to iterate over all entries.
Changed in version 3.7:
Dictionary order is guaranteed to be insertion order.
in
dictview
Return
True
if
is in the underlying dictionary’s keys, values or
items (in the latter case,
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.
Added in version 3.10.
Keys views are set-like since their entries are unique and
hashable
Items views also have set-like operations since the (key, value) pairs
are unique and the keys are hashable.
If all values in an items view are hashable as well,
then the items view can interoperate with other sets.
(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
). While using set operators,
set-like views accept any iterable as the other operand,
unlike sets which only accept sets as the input.
An example of dictionary view usage:
>>>
dishes
'eggs'
'sausage'
'bacon'
'spam'
500
>>>
keys
dishes
keys
()
>>>
values
dishes
values
()
>>>
# iteration
>>>
>>>
for
val
in
values
...
+=
val
...
>>>
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'
True
>>>
keys
'juice'
'juice'
'juice'
==
'bacon'
'spam'
'juice'
True
>>>
# get back a read-only proxy for the original dictionary
>>>
values
mapping
mappingproxy({'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 of
with
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 a
with
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 the
with
statement without affecting code outside the
with
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 are
None
Returning a true value from this method will cause the
with
statement
to suppress the exception and continue execution with the statement immediately
following the
with
statement. Otherwise the exception continues
propagating after this method has finished executing.
If this method raises an exception while handling an earlier exception from the
with
block, the new exception is raised, and the original exception
is stored in its
__context__
attribute.
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
generator
s 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__()
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
re.search('foo',
'foo')
will be a
re.Match
object where the return values of
x.group(0)
and
x[0]
will both be of type
str
. We can
represent this kind of object in type annotations with the
GenericAlias
re.Match[str]
If
re.search(b'bar',
b'bar')
, (note the
for
bytes
),
will also be an instance of
re.Match
, but the return
values of
y.group(0)
and
y[0]
will both be of type
bytes
. In type annotations, we would represent this
variety of
re.Match
objects with
re.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 type
parameterized by types
, and more depending on the
used.
For example, a function expecting a
list
containing
float
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 a
dict
with
keys of type
str
and values of type
int
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
([
],
list
str
])
Traceback (most recent call last):
File
""
, line
, 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:
>>>
list
str
>>>
([
])
[1, 2, 3]
Furthermore, parameterized generics erase type parameters during object
creation:
>>>
list
str
>>>
type

>>>
()
>>>
type

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):
...
TypeError
dict[str] is not a generic class
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
>>>
TypeVar
'Y'
>>>
dict
str
][
int
dict[str, int]
Standard Generic Classes
The following standard library classes support parameterized generics. This
list is non-exhaustive.
tuple
list
dict
set
frozenset
type
asyncio.Future
asyncio.Task
collections.deque
collections.defaultdict
collections.OrderedDict
collections.Counter
collections.ChainMap
collections.abc.Awaitable
collections.abc.Coroutine
collections.abc.AsyncIterable
collections.abc.AsyncIterator
collections.abc.AsyncGenerator
collections.abc.Iterable
collections.abc.Iterator
collections.abc.Generator
collections.abc.Reversible
collections.abc.Container
collections.abc.Collection
collections.abc.Callable
collections.abc.Set
collections.abc.MutableSet
collections.abc.Mapping
collections.abc.MutableMapping
collections.abc.Sequence
collections.abc.MutableSequence
collections.abc.ByteString
collections.abc.MappingView
collections.abc.KeysView
collections.abc.ItemsView
collections.abc.ValuesView
contextlib.AbstractContextManager
contextlib.AbstractAsyncContextManager
dataclasses.Field
functools.cached_property
functools.partialmethod
os.PathLike
queue.LifoQueue
queue.Queue
queue.PriorityQueue
queue.SimpleQueue
re.Pattern
re.Match
shelve.BsdDbShelf
shelve.DbfilenameShelf
shelve.Shelf
types.MappingProxyType
weakref.WeakKeyDictionary
weakref.WeakMethod
weakref.WeakSet
weakref.WeakValueDictionary
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__

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__
(, list[int])
genericalias.
__parameters__
This attribute is a lazily computed tuple (possibly empty) of unique type
variables found in
__args__
>>>
from
typing
import
TypeVar
>>>
TypeVar
'T'
>>>
list
__parameters__
(~T,)
Note
GenericAlias
object with
typing.ParamSpec
parameters may not
have correct
__parameters__
after substitution because
typing.ParamSpec
is intended primarily for static type checking.
genericalias.
__unpacked__
A boolean that is true if the alias has been unpacked using the
operator (see
TypeVarTuple
).
Added in version 3.11.
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.
Added 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 subscripting
typing.Union
...
Defines a union object which holds types
, and so forth.
means either X or Y. It is equivalent to
typing.Union[X,
Y]
For example, the following function expects an argument of type
int
or
float
def
square
number
int
float
->
int
float
return
number
**
Note
The
operand cannot be used at runtime to define unions where one or
more members is a forward reference. For example,
int
"Foo"
, where
"Foo"
is a reference to a class not yet defined, will fail at
runtime. For unions which include forward references, present the
whole expression as a string, e.g.
"int
Foo"
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 creates instances of
typing.Union
int
str
==
typing
Union
int
str
type
int
str
is
typing
Union
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()
and
issubclass()
are also supported with a
union object:
>>>
isinstance
""
int
str
True
However,
parameterized generics
in
union objects cannot be checked:
>>>
isinstance
int
list
int
])
# short-circuit evaluation
True
>>>
isinstance
([
],
int
list
int
])
Traceback (most recent call last):
...
TypeError
isinstance() argument 2 cannot be a parameterized generic
The user-exposed type for the union object can be accessed from
typing.Union
and used for
isinstance()
checks:
>>>
import
typing
>>>
isinstance
int
str
typing
Union
True
>>>
typing
Union
()
Traceback (most recent call last):
File
""
, line
, in

TypeError
cannot create 'typing.Union' instances
Note
The
__or__()
method for type objects was added to support the syntax
. If a metaclass implements
__or__()
, the Union may
override it:
>>>
class
type
):
...
def
__or__
self
other
):
...
return
"Hello"
...
>>>
class
metaclass
):
...
pass
...
>>>
int
'Hello'
>>>
int
int | C
See also
PEP 604
– PEP proposing the
syntax and the Union type.
Added in version 3.10.
Changed in version 3.14:
Union objects are now instances of
typing.Union
. Previously, they were instances
of
types.UnionType
, which remains an alias for
typing.Union
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
is a module and
name
accesses a name defined in
’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']
, which defines
m.a
to be
, but you can’t write
m.__dict__
{}
). Modifying
__dict__
directly is
not recommended.
Modules built into the interpreter are written like this:
'sys'
(built-in)>
. If loaded from a file, they are written as
'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 method
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 (
method.__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
...
def
method
self
):
...
pass
...
>>>
()
>>>
method
whoami
'my name is method'
# can't set on the method
Traceback (most recent call last):
File
""
, line
, in

AttributeError
'method' object has no attribute 'whoami'
>>>
method
__func__
whoami
'my name is method'
>>>
method
whoami
'my name is method'
See
Instance methods
for more information.
Code Objects
Code objects are used by the implementation to represent “pseudo-compiled”
executable Python code such as a function body. They differ from function
objects because they don’t contain a reference to their global execution
environment. Code objects are returned by the built-in
compile()
function
and can be extracted from function objects through their
__code__
attribute. See also the
code
module.
Accessing
__code__
raises an
auditing event
object.__getattr__
with arguments
obj
and
"__code__"
A code object can be executed or evaluated by passing it (instead of a source
string) to the
exec()
or
eval()
built-in functions.
See
The standard type hierarchy
for more information.
Type Objects
Type objects represent the various object types. An object’s type is accessed
by the built-in function
type()
. There are no special operations on
types. The standard module
types
defines names for all standard built-in
types.
Types are written like this:
'int'>
The Null Object
This object is returned by functions that don’t explicitly return a value. It
supports no special operations. There is exactly one null object, named
None
(a built-in name).
type(None)()
produces the same singleton.
It is written as
None
The Ellipsis Object
This object is commonly used to indicate that something is omitted.
It supports no special operations. There is exactly one ellipsis object, named
Ellipsis
(a built-in name).
type(Ellipsis)()
produces the
Ellipsis
singleton.
It is written as
Ellipsis
or
...
In typical use,
...
as the
Ellipsis
object appears in a few different
places, for instance:
In type annotations, such as
callable arguments
or
tuple elements
As the body of a function instead of a
pass statement
In third-party libraries, such as
Numpy’s slicing and striding
Python also uses three dots in ways that are not
Ellipsis
objects, for instance:
Doctest’s
ELLIPSIS
, as a pattern for missing content.
The default Python prompt of the
interactive
shell when partial input is incomplete.
Lastly, the Python documentation often uses three dots in conventional English
usage to mean omitted content, even in code examples that also use them as the
Ellipsis
The NotImplemented Object
This object is returned from comparisons and binary operations when they are
asked to operate on types they don’t support. See
Comparisons
for more
information. There is exactly one
NotImplemented
object.
type(NotImplemented)()
produces the singleton instance.
It is written as
NotImplemented
Internal Objects
See
The standard type hierarchy
for this information. It describes
stack frame objects
traceback objects
, and slice objects.
Special Attributes
The implementation adds a few special read-only attributes to several object
types, where they are relevant. Some of these are not reported by the
dir()
built-in function.
definition.
__name__
The name of the class, function, method, descriptor, or
generator instance.
definition.
__qualname__
The
qualified name
of the class, function, method, descriptor,
or generator instance.
Added in version 3.3.
definition.
__module__
The name of the module in which a class or function was defined.
definition.
__doc__
The documentation string of a class or function, or
None
if undefined.
definition.
__type_params__
The
type parameters
of generic classes, functions,
and
type aliases
. For classes and functions that
are not generic, this will be an empty tuple.
Added in version 3.12.
Integer string conversion length limitation
CPython has a global limit for converting between
int
and
str
to mitigate denial of service attacks. This limit
only
applies to decimal or
other non-power-of-two number bases. Hexadecimal, octal, and binary conversions
are unlimited. The limit can be configured.
The
int
type in CPython is an arbitrary length number stored in binary
form (commonly known as a “bignum”). There exists no algorithm that can convert
a string to a binary integer or a binary integer to a string in linear time,
unless
the base is a power of 2. Even the best known algorithms for base 10
have sub-quadratic complexity. Converting a large value such as
int('1'
500_000)
can take over a second on a fast CPU.
Limiting conversion size offers a practical way to avoid
CVE 2020-10735
The limit is applied to the number of digit characters in the input or output
string when a non-linear conversion algorithm would be involved. Underscores
and the sign are not counted towards the limit.
When an operation would exceed the limit, a
ValueError
is raised:
>>>
import
sys
>>>
sys
set_int_max_str_digits
4300
# Illustrative, this is the default.
>>>
int
'2'
5432
Traceback (most recent call last):
...
ValueError
Exceeds the limit (4300 digits) for integer string conversion: value has 5432 digits; use sys.set_int_max_str_digits() to increase the limit
>>>
int
'2'
4300
>>>
len
str
))
4300
>>>
i_squared
>>>
len
str
i_squared
))
Traceback (most recent call last):
...
ValueError
Exceeds the limit (4300 digits) for integer string conversion; use sys.set_int_max_str_digits() to increase the limit
>>>
len
hex
i_squared
))
7144
>>>
assert
int
hex
i_squared
),
base
16
==
# Hexadecimal is unlimited.
The default limit is 4300 digits as provided in
sys.int_info.default_max_str_digits
The lowest limit that can be configured is 640 digits as provided in
sys.int_info.str_digits_check_threshold
Verification:
>>>
import
sys
>>>
assert
sys
int_info
default_max_str_digits
==
4300
sys
int_info
>>>
assert
sys
int_info
str_digits_check_threshold
==
640
sys
int_info
>>>
msg
int
'578966293710682886880994035146873798396722250538762761564'
...
'9252925514383915483333812743580549779436104706260696366600'
...
'571186405732'
to_bytes
53
'big'
...
Added in version 3.11.
Affected APIs
The limitation only applies to potentially slow conversions between
int
and
str
or
bytes
int(string)
with default base 10.
int(string,
base)
for all bases that are not a power of 2.
str(integer)
repr(integer)
any other string conversion to base 10, for example
f"{integer}"
"{}".format(integer)
, or
b"%d"
integer
The limitations do not apply to functions with a linear algorithm:
int(string,
base)
with base 2, 4, 8, 16, or 32.
int.from_bytes()
and
int.to_bytes()
hex()
oct()
bin()
Format specification mini-language
for hex, octal, and binary numbers.
str
to
float
str
to
decimal.Decimal
Configuring the limit
Before Python starts up you can use an environment variable or an interpreter
command line flag to configure the limit:
PYTHONINTMAXSTRDIGITS
, e.g.
PYTHONINTMAXSTRDIGITS=640
python3
to set the limit to 640 or
PYTHONINTMAXSTRDIGITS=0
python3
to disable the limitation.
-X
int_max_str_digits
, e.g.
python3
-X
int_max_str_digits=640
sys.flags.int_max_str_digits
contains the value of
PYTHONINTMAXSTRDIGITS
or
-X
int_max_str_digits
If both the env var and the
-X
option are set, the
-X
option takes
precedence. A value of
-1
indicates that both were unset, thus a value of
sys.int_info.default_max_str_digits
was used during initialization.
From code, you can inspect the current limit and set a new one using these
sys
APIs:
sys.get_int_max_str_digits()
and
sys.set_int_max_str_digits()
are
a getter and setter for the interpreter-wide limit. Subinterpreters have
their own limit.
Information about the default and minimum can be found in
sys.int_info
sys.int_info.default_max_str_digits
is the compiled-in
default limit.
sys.int_info.str_digits_check_threshold
is the lowest
accepted value for the limit (other than 0 which disables it).
Added in version 3.11.
Caution
Setting a low limit
can
lead to problems. While rare, code exists that
contains integer constants in decimal in their source that exceed the
minimum threshold. A consequence of setting the limit is that Python source
code containing decimal integer literals longer than the limit will
encounter an error during parsing, usually at startup time or import time or
even at installation time - anytime an up to date
.pyc
does not already
exist for the code. A workaround for source that contains such large
constants is to convert them to
0x
hexadecimal form as it has no limit.
Test your application thoroughly if you use a low limit. Ensure your tests
run with the limit set early via the environment or flag so that it applies
during startup and even during any installation step that may invoke Python
to precompile
.py
sources to
.pyc
files.
Recommended configuration
The default
sys.int_info.default_max_str_digits
is expected to be
reasonable for most applications. If your application requires a different
limit, set it from your main entry point using Python version agnostic code as
these APIs were added in security patch releases in versions before 3.12.
Example:
>>>
import
sys
>>>
if
hasattr
sys
"set_int_max_str_digits"
):
...
upper_bound
68000
...
lower_bound
4004
...
current_limit
sys
get_int_max_str_digits
()
...
if
current_limit
==
or
current_limit
upper_bound
...
sys
set_int_max_str_digits
upper_bound
...
elif
current_limit
lower_bound
...
sys
set_int_max_str_digits
lower_bound
If you need to disable it entirely, set it to
Footnotes
Additional information on these special methods may be found in the Python
Reference Manual (
Basic customization
).
As a consequence, the list
[1,
2]
is considered equal to
[1.0,
2.0]
, and
similarly for tuples.
They must have since the parser can’t tell the type of the operands.
Cased characters are those with general category property being one of
“Lu” (Letter, uppercase), “Ll” (Letter, lowercase), or “Lt” (Letter, titlecase).
To format only a tuple you should therefore provide a singleton tuple whose only
element is the tuple to be formatted.
Table of Contents
Built-in Types
Truth Value Testing
Boolean Operations —
and
or
not
Comparisons
Numeric Types —
int
float
complex
Bitwise Operations on Integer Types
Additional Methods on Integer Types
Additional Methods on Float
Additional Methods on Complex
Hashing of numeric types
Boolean Type -
bool
Iterator Types
Generator Types
Sequence Types —
list
tuple
range
Common Sequence Operations
Immutable Sequence Types
Mutable Sequence Types
Lists
Tuples
Ranges
Text and Binary Sequence Type Methods Summary
Text Sequence Type —
str
String Methods
Formatted String Literals (f-strings)
Debug specifier
Conversion specifier
Format specifier
Template String Literals (t-strings)
printf
-style String Formatting
Binary Sequence Types —
bytes
bytearray
memoryview
Bytes Objects
Bytearray Objects
Bytes and Bytearray Operations
printf
-style Bytes Formatting
Memory Views
Set Types —
set
frozenset
Mapping Types —
dict
Dictionary view objects
Context Manager Types
Type Annotation Types —
Generic Alias
Union
Generic Alias Type
Standard Generic Classes
Special Attributes of
GenericAlias
objects
Union Type
Other Built-in Types
Modules
Classes and Class Instances
Functions
Methods
Code Objects
Type Objects
The Null Object
The Ellipsis Object
The NotImplemented Object
Internal Objects
Special Attributes
Integer string conversion length limitation
Affected APIs
Configuring the limit
Recommended configuration
Previous topic
Built-in Constants
Next topic
Built-in Exceptions
This page
Report a bug
Improve this page
Show source
index
modules
next
previous
Python
3.14.4 Documentation
The Python Standard Library
Built-in Types
Theme
2001 Python Software Foundation.
This page is licensed under the Python Software Foundation License Version 2.
Examples, recipes, and other code in the documentation are additionally licensed under the Zero Clause BSD License.
See
History and License
for more information.
The Python Software Foundation is a non-profit corporation.
Please donate.
Found a bug
Created using
Sphinx
8.2.3.