Built-in Types¶
The following sections describe the standard types that are built into the interpreter.
The principal built-in types are numerics, sequences, mappings, classes, instances and exceptions.
Some collection classes are mutable. The methods that add, subtract, or
rearrange their members in place, and don’t return a specific item, never return
the collection instance itself but None
.
Some operations are supported by several object types; in particular,
practically all objects can be compared for equality, tested for truth
value, and converted to a string (with the repr()
function or the
slightly different str()
function). The latter function is implicitly
used when an object is written by the print()
function.
Truth Value Testing¶
Any object can be tested for truth value, for use in an if
or
while
condition or as operand of the Boolean operations below.
By default, an object is considered true unless its class defines either a
__bool__()
method that returns False
or a
__len__()
method that
returns zero, when called with the object. [1] Here are most of the built-in
objects considered false:
constants defined to be false:
None
andFalse
zero of any numeric type:
0
,0.0
,0j
,Decimal(0)
,Fraction(0, 1)
empty sequences and collections:
''
,()
,[]
,{}
,set()
,range(0)
Operations and built-in functions that have a Boolean result always return 0
or False
for false and 1
or True
for true, unless otherwise stated.
(Important exception: the Boolean operations or
and and
always return
one of their operands.)
Boolean Operations — and
, or
, not
¶
These are the Boolean operations, ordered by ascending priority:
Operation |
Result |
Notes |
---|---|---|
|
if x is true, then x, else y |
(1) |
|
if x is false, then x, else y |
(2) |
|
if x is false, then |
(3) |
Notes:
This is a short-circuit operator, so it only evaluates the second argument if the first one is false.
This is a short-circuit operator, so it only evaluates the second argument if the first one is true.
not
has a lower priority than non-Boolean operators, sonot a == b
is interpreted asnot (a == b)
, anda == not b
is a syntax error.
Comparisons¶
There are eight comparison operations in Python. They all have the same
priority (which is higher than that of the Boolean operations). Comparisons can
be chained arbitrarily; for example, x < y <= z
is equivalent to x < y and
y <= z
, except that y is evaluated only once (but in both cases z is not
evaluated at all when x < y
is found to be false).
This table summarizes the comparison operations:
Operation |
Meaning |
---|---|
|
strictly less than |
|
less than or equal |
|
strictly greater than |
|
greater than or equal |
|
equal |
|
not equal |
|
object identity |
|
negated object identity |
Objects of different types, except different numeric types, never compare equal.
The ==
operator is always defined but for some object types (for example,
class objects) is equivalent to is
. The <
, <=
, >
and >=
operators are only defined where they make sense; for example, they raise a
TypeError
exception when one of the arguments is a complex number.
Non-identical instances of a class normally compare as non-equal unless the
class defines the __eq__()
method.
Instances of a class cannot be ordered with respect to other instances of the
same class, or other types of object, unless the class defines enough of the
methods __lt__()
, __le__()
, __gt__()
, and
__ge__()
(in general, __lt__()
and
__eq__()
are sufficient, if you want the conventional meanings of the
comparison operators).
The behavior of the is
and is not
operators cannot be
customized; also they can be applied to any two objects and never raise an
exception.
Two more operations with the same syntactic priority, in
and
not in
, are supported by types that are iterable or
implement the __contains__()
method.
Numeric Types — int
, float
, complex
¶
There are three distinct numeric types: integers, floating-point
numbers, and complex numbers. In addition, Booleans are a
subtype of integers. Integers have unlimited precision. Floating-point
numbers are usually implemented using double in C; information
about the precision and internal representation of floating-point
numbers for the machine on which your program is running is available
in sys.float_info
. Complex numbers have a real and imaginary
part, which are each a floating-point number. To extract these parts
from a complex number z, use z.real
and z.imag
. (The standard
library includes the additional numeric types fractions.Fraction
, for
rationals, and decimal.Decimal
, for floating-point numbers with
user-definable precision.)
Numbers are created by numeric literals or as the result of built-in functions
and operators. Unadorned integer literals (including hex, octal and binary
numbers) yield integers. Numeric literals containing a decimal point or an
exponent sign yield floating-point numbers. Appending 'j'
or 'J'
to a
numeric literal yields an imaginary number (a complex number with a zero real
part) which you can add to an integer or float to get a complex number with real
and imaginary parts.
Python fully supports mixed arithmetic: when a binary arithmetic operator has operands of different numeric types, the operand with the “narrower” type is widened to that of the other, where integer is narrower than floating point, which is narrower than complex. A comparison between numbers of different types behaves as though the exact values of those numbers were being compared. [2]
The constructors int()
, float()
, and
complex()
can be used to produce numbers of a specific type.
All numeric types (except complex) support the following operations (for priorities of the operations, see Operator precedence):
Operation |
Result |
Notes |
Full documentation |
---|---|---|---|
|
sum of x and y |
||
|
difference of x and y |
||
|
product of x and y |
||
|
quotient of x and y |
||
|
floored quotient of x and y |
(1)(2) |
|
|
remainder of |
(2) |
|
|
x negated |
||
|
x unchanged |
||
|
absolute value or magnitude of x |
||
|
x converted to integer |
(3)(6) |
|
|
x converted to floating point |
(4)(6) |
|
|
a complex number with real part re, imaginary part im. im defaults to zero. |
(6) |
|
|
conjugate of the complex number c |
||
|
the pair |
(2) |
|
|
x to the power y |
(5) |
|
|
x to the power y |
(5) |
Notes:
Also referred to as integer division. For operands of type
int
, the result has typeint
. For operands of typefloat
, the result has typefloat
. In general, the result is a whole integer, though the result’s type is not necessarilyint
. The result is always rounded towards minus infinity:1//2
is0
,(-1)//2
is-1
,1//(-2)
is-1
, and(-1)//(-2)
is0
.Not for complex numbers. Instead convert to floats using
abs()
if appropriate.Conversion from
float
toint
truncates, discarding the fractional part. See functionsmath.floor()
andmath.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)
and0 ** 0
to be1
, as is common for programming languages.The numeric literals accepted include the digits
0
to9
or any Unicode equivalent (code points with theNd
property).See 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 |
---|---|
x truncated to |
|
x rounded to n digits, rounding half to even. If n is omitted, it defaults to 0. |
|
the greatest |
|
the least |
For additional numeric operations see the math
and cmath
modules.
Bitwise Operations on Integer Types¶
Bitwise operations only make sense for integers. The result of bitwise operations is calculated as though carried out in two’s complement with an infinite number of sign bits.
The priorities of the binary bitwise operations are all lower than the numeric
operations and higher than the comparisons; the unary operation ~
has the
same priority as the other unary numeric operations (+
and -
).
This table lists the bitwise operations sorted in ascending priority:
Operation |
Result |
Notes |
---|---|---|
|
bitwise or of x and y |
(4) |
|
bitwise exclusive or of x and y |
(4) |
|
bitwise and of x and y |
(4) |
|
x shifted left by n bits |
(1)(2) |
|
x shifted right by n bits |
(1)(3) |
|
the bits of x inverted |
Notes:
Negative shift counts are illegal and cause a
ValueError
to be raised.A left shift by n bits is equivalent to multiplication by
pow(2, n)
.A right shift by n bits is equivalent to floor division by
pow(2, n)
.Performing these calculations with at least one extra sign extension bit in a finite two’s complement representation (a working bit-width of
1 + max(x.bit_length(), y.bit_length())
or more) is sufficient to get the same result as if there were an infinite number of sign bits.
Additional Methods on Integer Types¶
The int type implements the numbers.Integral
abstract base
class. In addition, it provides a few more methods:
- int.bit_length()¶
Return the number of bits necessary to represent an integer in binary, excluding the sign and leading zeros:
>>> n = -37 >>> bin(n) '-0b100101' >>> n.bit_length() 6
More precisely, if
x
is nonzero, thenx.bit_length()
is the unique positive integerk
such that2**(k-1) <= abs(x) < 2**k
. Equivalently, whenabs(x)
is small enough to have a correctly rounded logarithm, thenk = 1 + int(log(abs(x), 2))
. Ifx
is zero, thenx.bit_length()
returns0
.Equivalent to:
def bit_length(self): s = bin(self) # binary representation: bin(-37) --> '-0b100101' s = s.lstrip('-0b') # remove leading zeros and minus sign return len(s) # len('100101') --> 6
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:
>>> n = 19 >>> bin(n) '0b10011' >>> n.bit_count() 3 >>> (-n).bit_count() 3
Equivalent to:
def bit_count(self): return bin(self).count("1")
Added in version 3.10.
- int.to_bytes(length=1, byteorder='big', *, signed=False)¶
Return an array of bytes representing an integer.
>>> (1024).to_bytes(2, byteorder='big') b'\x04\x00' >>> (1024).to_bytes(10, byteorder='big') b'\x00\x00\x00\x00\x00\x00\x00\x00\x04\x00' >>> (-1024).to_bytes(10, byteorder='big', signed=True) b'\xff\xff\xff\xff\xff\xff\xff\xff\xfc\x00' >>> x = 1000 >>> x.to_bytes((x.bit_length() + 7) // 8, byteorder='little') b'\xe8\x03'
The integer is represented using length bytes, 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, anOverflowError
is raised. The default value for signed isFalse
.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(n, length=1, 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((n >> i*8) & 0xff for i in order)
Added in version 3.2.
Changed in version 3.11: Added default argument values for
length
andbyteorder
.
- classmethod int.from_bytes(bytes, byteorder='big', *, signed=False)¶
Return the integer represented by the given array of bytes.
>>> int.from_bytes(b'\x00\x10', byteorder='big') 16 >>> int.from_bytes(b'\x00\x10', byteorder='little') 4096 >>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=True) -1024 >>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=False) 64512 >>> int.from_bytes([255, 0, 0], byteorder='big') 16711680
The argument bytes must either be a bytes-like object or an iterable producing bytes.
The byteorder argument determines the byte order used to represent the integer, 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, usesys.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'") n = sum(b << i*8 for i, b in enumerate(little_ordered)) if signed and little_ordered and (little_ordered[-1] & 0x80): n -= 1 << 8*len(little_ordered) return n
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
1
as the denominator.Added in version 3.8.
- int.is_integer()¶
Returns
True
. Exists for duck type compatibility withfloat.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.
- 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 aValueError
on NaNs.
- float.is_integer()¶
Return
True
if the float instance is finite with integral value, andFalse
otherwise:>>> (-2.0).is_integer() True >>> (3.2).is_integer() False
Two methods support conversion to and from hexadecimal strings. Since Python’s floats are stored internally as binary numbers, converting a float to or from a decimal string usually involves a small rounding error. In contrast, hexadecimal strings allow exact representation and specification of floating-point numbers. This can be useful when debugging, and in numerical work.
- float.hex()¶
Return a representation of a floating-point number as a hexadecimal string. For finite floating-point numbers, this representation will always include a leading
0x
and a trailingp
and exponent.
- classmethod float.fromhex(s)¶
Class method to return the float represented by a hexadecimal string s. The string s may have leading and trailing whitespace.
Note that float.hex()
is an instance method, while
float.fromhex()
is a class method.
A hexadecimal string takes the form:
[sign] ['0x'] integer ['.' fraction] ['p' exponent]
where the optional sign
may by either +
or -
, integer
and fraction
are strings of hexadecimal digits, and exponent
is a decimal integer with an optional leading sign. Case is not
significant, and there must be at least one hexadecimal digit in
either the integer or the fraction. This syntax is similar to the
syntax specified in section 6.4.4.2 of the C99 standard, and also to
the syntax used in Java 1.5 onwards. In particular, the output of
float.hex()
is usable as a hexadecimal floating-point literal in
C or Java code, and hexadecimal strings produced by C’s %a
format
character or Java’s Double.toHexString
are accepted by
float.fromhex()
.
Note that the exponent is written in decimal rather than hexadecimal,
and that it gives the power of 2 by which to multiply the coefficient.
For example, the hexadecimal string 0x3.a7p10
represents the
floating-point number (3 + 10./16 + 7./16**2) * 2.0**10
, or
3740.0
:
>>> float.fromhex('0x3.a7p10')
3740.0
Applying the reverse conversion to 3740.0
gives a different
hexadecimal string representing the same number:
>>> float.hex(3740.0)
'0x1.d380000000000p+11'
Hashing of numeric types¶
For numbers x
and y
, possibly of different types, it’s a requirement
that hash(x) == hash(y)
whenever x == y
(see the __hash__()
method documentation for more details). For ease of implementation and
efficiency across a variety of numeric types (including int
,
float
, decimal.Decimal
and fractions.Fraction
)
Python’s hash for numeric types is based on a single mathematical function
that’s defined for any rational number, and hence applies to all instances of
int
and fractions.Fraction
, and all finite instances of
float
and decimal.Decimal
. Essentially, this function is
given by reduction modulo P
for a fixed prime P
. The value of P
is
made available to Python as the modulus
attribute of
sys.hash_info
.
CPython implementation detail: Currently, the prime used is P = 2**31 - 1
on machines with 32-bit C
longs and P = 2**61 - 1
on machines with 64-bit C longs.
Here are the rules in detail:
If
x = m / n
is a nonnegative rational number andn
is not divisible byP
, definehash(x)
asm * invmod(n, P) % P
, whereinvmod(n, P)
gives the inverse ofn
moduloP
.If
x = m / n
is a nonnegative rational number andn
is divisible byP
(butm
is not) thenn
has no inverse moduloP
and the rule above doesn’t apply; in this case definehash(x)
to be the constant valuesys.hash_info.inf
.If
x = m / n
is a negative rational number definehash(x)
as-hash(-x)
. If the resulting hash is-1
, replace it with-2
.The particular values
sys.hash_info.inf
and-sys.hash_info.inf
are used as hash values for positive infinity or negative infinity (respectively).For a
complex
numberz
, the hash values of the real and imaginary parts are combined by computinghash(z.real) + sys.hash_info.imag * hash(z.imag)
, reduced modulo2**sys.hash_info.width
so that it lies inrange(-2**(sys.hash_info.width - 1), 2**(sys.hash_info.width - 1))
. Again, if the result is-1
, it’s replaced with-2
.
To clarify the above rules, here’s some example Python code,
equivalent to the built-in hash, for computing the hash of a rational
number, float
, or complex
:
import sys, math
def hash_fraction(m, n):
"""Compute the hash of a rational number m / n.
Assumes m and n are integers, with n positive.
Equivalent to hash(fractions.Fraction(m, n)).
"""
P = sys.hash_info.modulus
# Remove common factors of P. (Unnecessary if m and n already coprime.)
while m % P == n % P == 0:
m, n = m // P, n // P
if n % P == 0:
hash_value = sys.hash_info.inf
else:
# Fermat's Little Theorem: pow(n, P-1, P) is 1, so
# pow(n, P-2, P) gives the inverse of n modulo P.
hash_value = (abs(m) % P) * pow(n, P - 2, P) % P
if m < 0:
hash_value = -hash_value
if hash_value == -1:
hash_value = -2
return hash_value
def hash_float(x):
"""Compute the hash of a float x."""
if math.isnan(x):
return object.__hash__(x)
elif math.isinf(x):
return sys.hash_info.inf if x > 0 else -sys.hash_info.inf
else:
return hash_fraction(*x.as_integer_ratio())
def hash_complex(z):
"""Compute the hash of a complex number z."""
hash_value = hash_float(z.real) + sys.hash_info.imag * hash_float(z.imag)
# do a signed reduction modulo 2**sys.hash_info.width
M = 2**(sys.hash_info.width - 1)
hash_value = (hash_value & (M - 1)) - (hash_value & M)
if hash_value == -1:
hash_value = -2
return hash_value
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
andin
statements. This method corresponds to thetp_iter
slot of the type structure for Python objects in the Python/C API.
- iterator.__next__()¶
Return the next item from the iterator. If there are no further items, raise the
StopIteration
exception. This method corresponds to thetp_iternext
slot of the type structure for Python objects in the Python/C API.
Python defines several iterator objects to support iteration over general and specific sequence types, dictionaries, and other more specialized forms. The specific types are not important beyond their implementation of the iterator protocol.
Once an iterator’s __next__()
method raises
StopIteration
, it must continue to do so on subsequent calls.
Implementations that do not obey this property are deemed broken.
Generator Types¶
Python’s generators provide a convenient way to implement the iterator
protocol. If a container object’s __iter__()
method is implemented as a
generator, it will automatically return an iterator object (technically, a
generator object) supplying the __iter__()
and __next__()
methods.
More information about generators can be found in the documentation for
the yield expression.
Sequence Types — list
, tuple
, range
¶
There are three basic sequence types: lists, tuples, and range objects. Additional sequence types tailored for processing of binary data and text strings are described in dedicated sections.
Common Sequence Operations¶
The operations in the following table are supported by most sequence types,
both mutable and immutable. The collections.abc.Sequence
ABC is
provided to make it easier to correctly implement these operations on
custom sequence types.
This table lists the sequence operations sorted in ascending priority. In the table, s and t are sequences of the same type, n, i, j and k are integers and x is an arbitrary object that meets any type and value restrictions imposed by s.
The in
and not in
operations have the same priorities as the
comparison operations. The +
(concatenation) and *
(repetition)
operations have the same priority as the corresponding numeric operations. [3]
Operation |
Result |
Notes |
---|---|---|
|
|
(1) |
|
|
(1) |
|
the concatenation of s and t |
(6)(7) |
|
equivalent to adding s to itself n times |
(2)(7) |
|
ith item of s, origin 0 |
(3) |
|
slice of s from i to j |
(3)(4) |
|
slice of s from i to j with step k |
(3)(5) |
|
length of s |
|
|
smallest item of s |
|
|
largest item of s |
|
|
index of the first occurrence of x in s (at or after index i and before index j) |
(8) |
|
total number of occurrences of x in s |
Sequences of the same type also support comparisons. In particular, tuples and lists are compared lexicographically by comparing corresponding elements. This means that to compare equal, every element must compare equal and the two sequences must be of the same type and have the same length. (For full details see Comparisons in the language reference.)
Forward and reversed iterators over mutable sequences access values using an
index. That index will continue to march forward (or backward) even if the
underlying sequence is mutated. The iterator terminates only when an
IndexError
or a StopIteration
is encountered (or when the index
drops below zero).
Notes:
While the
in
andnot in
operations are used only for simple containment testing in the general case, some specialised sequences (such asstr
,bytes
andbytearray
) also use them for subsequence testing:>>> "gg" in "eggs" True
Values of n less than
0
are treated as0
(which yields an empty sequence of the same type as s). Note that items in the sequence s are not copied; they are referenced multiple times. This often haunts new Python programmers; consider:>>> lists = [[]] * 3 >>> lists [[], [], []] >>> lists[0].append(3) >>> lists [[3], [3], [3]]
What has happened is that
[[]]
is a one-element list containing an empty list, so all three elements of[[]] * 3
are references to this single empty list. Modifying any of the elements oflists
modifies this single list. You can create a list of different lists this way:>>> lists = [[] for i in range(3)] >>> lists[0].append(3) >>> lists[1].append(5) >>> lists[2].append(7) >>> lists [[3], [5], [7]]
Further explanation is available in the FAQ entry How do I create a multidimensional list?.
If i or j is negative, the index is relative to the end of sequence s:
len(s) + i
orlen(s) + j
is substituted. But note that-0
is still0
.The slice of s from i to j is defined as the sequence of items with index k such that
i <= k < j
. If i or j is greater thanlen(s)
, uselen(s)
. If i is omitted orNone
, use0
. If j is omitted orNone
, uselen(s)
. If i is greater than or equal to j, the slice is empty.The slice of s from i to j with step k is defined as the sequence of items with index
x = i + n*k
such that0 <= n < (j-i)/k
. In other words, the indices arei
,i+k
,i+2*k
,i+3*k
and so on, stopping when j is reached (but never including j). When k is positive, i and j are reduced tolen(s)
if they are greater. When k is negative, i and j are reduced tolen(s) - 1
if they are greater. If i or j are omitted orNone
, they become “end” values (which end depends on the sign of k). Note, k cannot be zero. If k isNone
, it is treated like1
.Concatenating immutable sequences always results in a new object. This means that building up a sequence by repeated concatenation will have a quadratic runtime cost in the total sequence length. To get a linear runtime cost, you must switch to one of the alternatives below:
if concatenating
str
objects, you can build a list and usestr.join()
at the end or else write to anio.StringIO
instance and retrieve its value when completeif concatenating
bytes
objects, you can similarly usebytes.join()
orio.BytesIO
, or you can do in-place concatenation with abytearray
object.bytearray
objects are mutable and have an efficient overallocation mechanismfor other types, investigate the relevant class documentation
Some sequence types (such as
range
) only support item sequences that follow specific patterns, and hence don’t support sequence concatenation or repetition.index
raisesValueError
when x is not found in s. Not all implementations support passing the additional arguments i and j. These arguments allow efficient searching of subsections of the sequence. Passing the extra arguments is roughly equivalent to usings[i:j].index(x)
, only without copying any data and with the returned index being relative to the start of the sequence rather than the start of the slice.
Immutable Sequence Types¶
The only operation that immutable sequence types generally implement that is
not also implemented by mutable sequence types is support for the hash()
built-in.
This support allows immutable sequences, such as tuple
instances, to
be used as dict
keys and stored in set
and frozenset
instances.
Attempting to hash an immutable sequence that contains unhashable values will
result in TypeError
.
Mutable Sequence Types¶
The operations in the following table are defined on mutable sequence types.
The collections.abc.MutableSequence
ABC is provided to make it
easier to correctly implement these operations on custom sequence types.
In the table s is an instance of a mutable sequence type, t is any
iterable object and x is an arbitrary object that meets any type
and value restrictions imposed by s (for example, bytearray
only
accepts integers that meet the value restriction 0 <= x <= 255
).
Operation |
Result |
Notes |
---|---|---|
|
item i of s is replaced by x |
|
|
slice of s from i to j is replaced by the contents of the iterable t |
|
|
same as |
|
|
the elements of |
(1) |
|
removes the elements of
|
|
|
appends x to the end of the
sequence (same as
|
|
|
removes all items from s
(same as |
(5) |
|
creates a shallow copy of s
(same as |
(5) |
|
extends s with the
contents of t (for the
most part the same as
|
|
|
updates s with its contents repeated n times |
(6) |
|
inserts x into s at the
index given by i
(same as |
|
|
retrieves the item at i and also removes it from s |
(2) |
|
removes the first item from
s where |
(3) |
|
reverses the items of s in place |
(4) |
Notes:
If k is not equal to
1
, t must have the same length as the slice it is replacing.The optional argument i defaults to
-1
, so that by default the last item is removed and returned.remove()
raisesValueError
when x is not found in s.The
reverse()
method modifies the sequence in place for economy of space when reversing a large sequence. To remind users that it operates by side effect, it does not return the reversed sequence.clear()
andcopy()
are included for consistency with the interfaces of mutable containers that don’t support slicing operations (such asdict
andset
).copy()
is not part of thecollections.abc.MutableSequence
ABC, but most concrete mutable sequence classes provide it.Added in version 3.3:
clear()
andcopy()
methods.The value n is an integer, or an object implementing
__index__()
. Zero and negative values of n clear the sequence. Items in the sequence are not copied; they are referenced multiple times, as explained fors * n
under Common Sequence Operations.
Lists¶
Lists are mutable sequences, typically used to store collections of homogeneous items (where the precise degree of similarity will vary by application).
- class list([iterable])¶
Lists may be constructed in several ways:
Using a pair of square brackets to denote the empty list:
[]
Using square brackets, separating items with commas:
[a]
,[a, b, c]
Using a list comprehension:
[x for x in iterable]
Using the type constructor:
list()
orlist(iterable)
The constructor builds a list whose items are the same and in the same order as iterable’s items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a list, a copy is made and returned, similar to
iterable[:]
. For example,list('abc')
returns['a', 'b', 'c']
andlist( (1, 2, 3) )
returns[1, 2, 3]
. If no argument is given, the constructor creates a new empty list,[]
.Many other operations also produce lists, including the
sorted()
built-in.Lists implement all of the common and mutable sequence operations. Lists also provide the following additional method:
- sort(*, key=None, reverse=False)¶
This method sorts the list in place, using only
<
comparisons between items. Exceptions are not suppressed - if any comparison operations fail, the entire sort operation will fail (and the list will likely be left in a partially modified state).sort()
accepts two arguments that can only be passed by keyword (keyword-only arguments):key specifies a function of one argument that is used to extract a comparison key from each list element (for example,
key=str.lower
). The key corresponding to each item in the list is calculated once and then used for the entire sorting process. The default value ofNone
means that list items are sorted directly without calculating a separate key value.The
functools.cmp_to_key()
utility is available to convert a 2.x style cmp function to a key function.reverse is a boolean value. If set to
True
, then the list elements are sorted as if each comparison were reversed.This method modifies the sequence in place for economy of space when sorting a large sequence. To remind users that it operates by side effect, it does not return the sorted sequence (use
sorted()
to explicitly request a new sorted list instance).The
sort()
method is guaranteed to be stable. A sort is stable if it guarantees not to change the relative order of elements that compare equal — this is helpful for sorting in multiple passes (for example, sort by department, then by salary grade).For sorting examples and a brief sorting tutorial, see Sorting 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.
Tuples¶
Tuples are immutable sequences, typically used to store collections of
heterogeneous data (such as the 2-tuples produced by the enumerate()
built-in). Tuples are also used for cases where an immutable sequence of
homogeneous data is needed (such as allowing storage in a set
or
dict
instance).
- class tuple([iterable])¶
Tuples may be constructed in a number of ways:
Using a pair of parentheses to denote the empty tuple:
()
Using a trailing comma for a singleton tuple:
a,
or(a,)
Separating items with commas:
a, b, c
or(a, b, c)
Using the
tuple()
built-in:tuple()
ortuple(iterable)
The constructor builds a tuple whose items are the same and in the same order as iterable’s items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a tuple, it is returned unchanged. For example,
tuple('abc')
returns('a', 'b', 'c')
andtuple( [1, 2, 3] )
returns(1, 2, 3)
. If no argument is given, the constructor creates a new empty tuple,()
.Note that it is actually the comma which makes a tuple, not the parentheses. The parentheses are optional, except in the empty tuple case, or when they are needed to avoid syntactic ambiguity. For example,
f(a, b, c)
is a function call with three arguments, whilef((a, b, c))
is a function call with a 3-tuple as the sole argument.Tuples implement all of the common sequence operations.
For heterogeneous collections of data where access by name is clearer than
access by index, collections.namedtuple()
may be a more appropriate
choice than a simple tuple object.
Ranges¶
The range
type represents an immutable sequence of numbers and is
commonly used for looping a specific number of times in for
loops.
- class range(stop)¶
- class range(start, stop[, step])
The arguments to the range constructor must be integers (either built-in
int
or any object that implements the__index__()
special method). If the step argument is omitted, it defaults to1
. If the start argument is omitted, it defaults to0
. If step is zero,ValueError
is raised.For a positive step, the contents of a range
r
are determined by the formular[i] = start + step*i
wherei >= 0
andr[i] < stop
.For a negative step, the contents of the range are still determined by the formula
r[i] = start + step*i
, but the constraints arei >= 0
andr[i] > stop
.A range object will be empty if
r[0]
does not meet the value constraint. Ranges do support negative indices, but these are interpreted as indexing from the end of the sequence determined by the positive indices.Ranges containing absolute values larger than
sys.maxsize
are permitted but some features (such aslen()
) may raiseOverflowError
.Range examples:
>>> list(range(10)) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> list(range(1, 11)) [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> list(range(0, 30, 5)) [0, 5, 10, 15, 20, 25] >>> list(range(0, 10, 3)) [0, 3, 6, 9] >>> list(range(0, -10, -1)) [0, -1, -2, -3, -4, -5, -6, -7, -8, -9] >>> list(range(0)) [] >>> list(range(1, 0)) []
Ranges implement all of the common sequence operations except concatenation and repetition (due to the fact that range objects can only represent sequences that follow a strict pattern and repetition and concatenation will usually violate that pattern).
- start¶
The value of the start parameter (or
0
if the parameter was not supplied)
- stop¶
The value of the stop parameter
- step¶
The value of the step parameter (or
1
if the parameter was not supplied)
The advantage of the range
type over a regular list
or
tuple
is that a range
object will always take the same
(small) amount of memory, no matter the size of the range it represents (as it
only stores the start
, stop
and step
values, calculating individual
items and subranges as needed).
Range objects implement the collections.abc.Sequence
ABC, and provide
features such as containment tests, element index lookup, slicing and
support for negative indices (see Sequence Types — list, tuple, range):
>>> r = range(0, 20, 2)
>>> r
range(0, 20, 2)
>>> 11 in r
False
>>> 10 in r
True
>>> r.index(10)
5
>>> r[5]
10
>>> r[:5]
range(0, 10, 2)
>>> r[-1]
18
Testing range objects for equality with ==
and !=
compares
them as sequences. That is, two range objects are considered equal if
they represent the same sequence of values. (Note that two range
objects that compare equal might have different start
,
stop
and step
attributes, for example
range(0) == range(2, 1, 3)
or range(0, 3, 2) == range(0, 4, 2)
.)
Changed in version 3.2: Implement the Sequence ABC.
Support slicing and negative indices.
Test int
objects for membership in constant time instead of
iterating through all items.
Changed in version 3.3: Define ‘==’ and ‘!=’ to compare range objects based on the sequence of values they define (instead of comparing based on object identity).
See also
The linspace recipe shows how to implement a lazy version of range suitable for floating-point applications.
Text Sequence Type — str
¶
Textual data in Python is handled with str
objects, or strings.
Strings are immutable
sequences of Unicode code points. String literals are
written in a variety of ways:
Single quotes:
'allows embedded "double" quotes'
Double quotes:
"allows embedded 'single' quotes"
Triple quoted:
'''Three single quotes'''
,"""Three double quotes"""
Triple quoted strings may span multiple lines - all associated whitespace will be included in the string literal.
String literals that are part of a single expression and have only whitespace
between them will be implicitly converted to a single string literal. That
is, ("spam " "eggs") == "spam eggs"
.
See String and Bytes literals for more about the various forms of string literal,
including supported escape sequences, and the r
(“raw”) prefix that
disables most escape sequence processing.
Strings may also be created from other objects using the str
constructor.
Since there is no separate “character” type, indexing a string produces
strings of length 1. That is, for a non-empty string s, s[0] == s[0:1]
.
There is also no mutable string type, but str.join()
or
io.StringIO
can be used to efficiently construct strings from
multiple fragments.
Changed in version 3.3: For backwards compatibility with the Python 2 series, the u
prefix is
once again permitted on string literals. It has no effect on the meaning
of string literals and cannot be combined with the r
prefix.
- class str(object='')¶
- class str(object=b'', encoding='utf-8', errors='strict')
Return a string version of object. If object is not provided, returns the empty string. Otherwise, the behavior of
str()
depends on whether encoding or errors is given, as follows.If neither encoding nor errors is given,
str(object)
returnstype(object).__str__(object)
, which is the “informal” or nicely printable string representation of object. For string objects, this is the string itself. If object does not have a__str__()
method, thenstr()
falls back to returningrepr(object)
.If at least one of encoding or errors is given, object should be a bytes-like object (e.g.
bytes
orbytearray
). In this case, if object is abytes
(orbytearray
) object, thenstr(bytes, encoding, errors)
is equivalent tobytes.decode(encoding, errors)
. Otherwise, the bytes object underlying the buffer object is obtained before callingbytes.decode()
. See Binary Sequence Types — bytes, bytearray, memoryview and Buffer Protocol for information on buffer objects.Passing a
bytes
object tostr()
without the encoding or errors arguments falls under the first case of returning the informal string representation (see also the-b
command-line option to Python). For example:>>> str(b'Zoot!') "b'Zoot!'"
For more information on the
str
class and its methods, see Text Sequence Type — str and the String Methods section below. To output formatted strings, see the 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"
.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)
.
- 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.
- 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), aUnicodeError
exception is raised. Other possible values are'ignore'
,'replace'
,'xmlcharrefreplace'
,'backslashreplace'
and any other name registered viacodecs.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.
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 returnFalse
. suffix can also be a tuple of suffixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.
- str.expandtabs(tabsize=8)¶
Return a copy of the string where all tab characters are replaced by one or more spaces, depending on the current column and the given tab size. Tab positions occur every tabsize characters (default is 8, giving tab positions at columns 0, 8, 16 and so on). To expand the string, the current column is set to zero and the string is examined character by character. If the character is a tab (
\t
), one or more space characters are inserted in the result until the current column is equal to the next tab position. (The tab character itself is not copied.) If the character is a newline (\n
) or return (\r
), it is copied and the current column is reset to zero. Any other character is copied unchanged and the current column is incremented by one regardless of how the character is represented when printed.>>> '01\t012\t0123\t01234'.expandtabs() '01 012 0123 01234' >>> '01\t012\t0123\t01234'.expandtabs(4) '01 012 0123 01234'
- str.find(sub[, start[, end]])¶
Return the lowest index in the string where substring sub is found within the slice
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
if sub is not found.
- str.format(*args, **kwargs)¶
Perform a string formatting operation. The string on which this method is called can contain literal text or replacement fields delimited by braces
{}
. Each replacement field contains either the numeric index of a positional argument, or the name of a keyword argument. Returns a copy of the string where each replacement field is replaced with the string value of the corresponding argument.>>> "The sum of 1 + 2 is {0}".format(1+2) 'The sum of 1 + 2 is 3'
See Format String Syntax for a description of the various formatting options that can be specified in format strings.
Note
When formatting a number (
int
,float
,complex
,decimal.Decimal
and subclasses) with then
type (ex:'{:n}'.format(1234)
), the function temporarily sets theLC_CTYPE
locale to theLC_NUMERIC
locale to decodedecimal_point
andthousands_sep
fields oflocaleconv()
if they are non-ASCII or longer than 1 byte, and theLC_NUMERIC
locale is different than theLC_CTYPE
locale. This temporary change affects other threads.Changed in version 3.7: When formatting a number with the
n
type, the function sets temporarily theLC_CTYPE
locale to theLC_NUMERIC
locale in some cases.
- str.format_map(mapping)¶
Similar to
str.format(**mapping)
, except thatmapping
is used directly and not copied to adict
. This is useful if for examplemapping
is a dict subclass:>>> class Default(dict): ... def __missing__(self, key): ... return key ... >>> '{name} was born in {country}'.format_map(Default(name='Guido')) 'Guido was born in country'
Added in version 3.2.
- str.index(sub[, start[, end]])¶
Like
find()
, but raiseValueError
when the substring is not found.
- str.isalnum()¶
Return
True
if all characters in the string are alphanumeric and there is at least one character,False
otherwise. A characterc
is alphanumeric if one of the following returnsTrue
:c.isalpha()
,c.isdecimal()
,c.isdigit()
, orc.isnumeric()
.
- str.isalpha()¶
Return
True
if all characters in the string are alphabetic and there is at least one character,False
otherwise. Alphabetic characters are those characters defined in the Unicode character database as “Letter”, i.e., those with general category property being one of “Lm”, “Lt”, “Lu”, “Ll”, or “Lo”. Note that this is different from the Alphabetic property defined in the section 4.10 ‘Letters, Alphabetic, and Ideographic’ of the Unicode Standard.
- str.isascii()¶
Return
True
if the string is empty or all characters in the string are ASCII,False
otherwise. ASCII characters have code points in the range U+0000-U+007F.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, e.g. U+0660, ARABIC-INDIC DIGIT ZERO. Formally a decimal character is a character in the Unicode General Category “Nd”.
- str.isdigit()¶
Return
True
if all characters in the string are digits and there is at least one character,False
otherwise. Digits include decimal characters and digits that need special handling, such as the compatibility superscript digits. This covers digits which cannot be used to form numbers in base 10, like the Kharosthi numbers. Formally, a digit is a character that has the property value Numeric_Type=Digit or Numeric_Type=Decimal.
- str.isidentifier()¶
Return
True
if the string is a valid identifier according to the language definition, section Identifiers and keywords.keyword.iskeyword()
can be used to test whether strings
is a reserved identifier, such asdef
andclass
.Example:
>>> from keyword import iskeyword >>> 'hello'.isidentifier(), iskeyword('hello') (True, False) >>> 'def'.isidentifier(), iskeyword('def') (True, True)
- str.islower()¶
Return
True
if all cased characters [4] in the string are lowercase and there is at least one cased character,False
otherwise.
- str.isnumeric()¶
Return
True
if all characters in the string are numeric characters, and there is at least one character,False
otherwise. Numeric characters include digit characters, and all characters that have the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION ONE FIFTH. Formally, numeric characters are those with the property value Numeric_Type=Digit, Numeric_Type=Decimal or Numeric_Type=Numeric.
- str.isprintable()¶
Return
True
if all characters in the string are printable or the string is empty,False
otherwise. Nonprintable characters are those characters defined in the Unicode character database as “Other” or “Separator”, excepting the ASCII space (0x20) which is considered printable. (Note that printable characters in this context are those which should not be escaped whenrepr()
is invoked on a string. It has no bearing on the handling of strings written tosys.stdout
orsys.stderr
.)
- str.isspace()¶
Return
True
if there are only whitespace characters in the string and there is at least one character,False
otherwise.A character is whitespace if in the Unicode character database (see
unicodedata
), either its general category isZs
(“Separator, space”), or its bidirectional class is one ofWS
,B
, orS
.
- str.istitle()¶
Return
True
if the string is a titlecased string and there is at least one character, for example uppercase characters may only follow uncased characters and lowercase characters only cased ones. ReturnFalse
otherwise.
- str.isupper()¶
Return
True
if all cased characters [4] in the string are uppercase and there is at least one cased character,False
otherwise.>>> 'BANANA'.isupper() True >>> 'banana'.isupper() False >>> 'baNana'.isupper() False >>> ' '.isupper() False
- str.join(iterable)¶
Return a string which is the concatenation of the strings in iterable. A
TypeError
will be raised if there are any non-string values in iterable, includingbytes
objects. The separator between elements is the string providing this method.
- str.ljust(width[, fillchar])¶
Return the string left justified in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to
len(s)
.
- str.lower()¶
Return a copy of the string with all the cased characters [4] converted to lowercase.
The lowercasing algorithm used is described in section 3.13 ‘Default Case Folding’ of the Unicode Standard.
- str.lstrip([chars])¶
Return a copy of the string with leading characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or
None
, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped:>>> ' spacious '.lstrip() 'spacious ' >>> 'www.example.com'.lstrip('cmowz.') 'example.com'
See
str.removeprefix()
for a method that will remove a single prefix string rather than all of a set of characters. For example:>>> 'Arthur: three!'.lstrip('Arthur: ') 'ee!' >>> 'Arthur: three!'.removeprefix('Arthur: ') 'three!'
- static str.maketrans(x[, y[, z]])¶
This static method returns a translation table usable for
str.translate()
.If there is only one argument, it must be a dictionary mapping Unicode ordinals (integers) or characters (strings of length 1) to Unicode ordinals, strings (of arbitrary lengths) or
None
. Character keys will then be converted to ordinals.If there are two arguments, they must be strings of equal length, and in the resulting dictionary, each character in x will be mapped to the character at the same position in y. If there is a third argument, it must be a string, whose characters will be mapped to
None
in the result.
- str.partition(sep)¶
Split the string at the first occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself, and the part after the separator. If the separator is not found, return a 3-tuple containing the string itself, followed by two empty strings.
- str.removeprefix(prefix, /)¶
If the string starts with the prefix string, return
string[len(prefix):]
. Otherwise, return a copy of the original string:>>> 'TestHook'.removeprefix('Test') 'Hook' >>> 'BaseTestCase'.removeprefix('Test') 'BaseTestCase'
Added in version 3.9.
- str.removesuffix(suffix, /)¶
If the string ends with the suffix string and that suffix is not empty, return
string[:-len(suffix)]
. Otherwise, return a copy of the original string:>>> 'MiscTests'.removesuffix('Tests') 'Misc' >>> 'TmpDirMixin'.removesuffix('Tests') 'TmpDirMixin'
Added in version 3.9.
- str.replace(old, new[, count])¶
Return a copy of the string with all occurrences of substring old replaced by new. If the optional argument count is given, only the first count occurrences are replaced.
- str.rfind(sub[, start[, end]])¶
Return the highest index in the string where substring sub is found, such that sub is contained within
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
on failure.
- str.rindex(sub[, start[, end]])¶
Like
rfind()
but raisesValueError
when the substring sub is not found.
- str.rjust(width[, fillchar])¶
Return the string right justified in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to
len(s)
.
- str.rpartition(sep)¶
Split the string at the last occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself, and the part after the separator. If the separator is not found, return a 3-tuple containing two empty strings, followed by the string itself.
- str.rsplit(sep=None, maxsplit=-1)¶
Return a list of the words in the string, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done, the rightmost ones. If sep is not specified or
None
, any whitespace string is a separator. Except for splitting from the right,rsplit()
behaves likesplit()
which is described in detail below.
- str.rstrip([chars])¶
Return a copy of the string with trailing characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or
None
, the chars argument defaults to removing whitespace. The chars argument is not a suffix; rather, all combinations of its values are stripped:>>> ' spacious '.rstrip() ' spacious' >>> 'mississippi'.rstrip('ipz') 'mississ'
See
str.removesuffix()
for a method that will remove a single suffix string rather than all of a set of characters. For example:>>> 'Monty Python'.rstrip(' Python') 'M' >>> 'Monty Python'.removesuffix(' Python') 'Monty'
- str.split(sep=None, maxsplit=-1)¶
Return a list of the words in the string, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done (thus, the list will have at most
maxsplit+1
elements). If maxsplit is not specified or-1
, then there is no limit on the number of splits (all possible splits are made).If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty strings (for example,
'1,,2'.split(',')
returns['1', '', '2']
). The sep argument may consist of multiple characters as a single delimiter (to split with multiple delimiters, usere.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) ['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 aNone
separator returns[]
.For example:
>>> '1 2 3'.split() ['1', '2', '3'] >>> '1 2 3'.split(maxsplit=1) ['1', '2 3'] >>> ' 1 2 3 '.split() ['1', '2', '3']
- str.splitlines(keepends=False)¶
Return a list of the lines in the string, breaking at line boundaries. Line breaks are not included in the resulting list unless keepends is given and true.
This method splits on the following line boundaries. In particular, the boundaries are a superset of universal newlines.
Representation
Description
\n
Line Feed
\r
Carriage Return
\r\n
Carriage Return + Line Feed
\v
or\x0b
Line Tabulation
\f
or\x0c
Form Feed
\x1c
File Separator
\x1d
Group Separator
\x1e
Record Separator
\x85
Next Line (C1 Control Code)
\u2028
Line Separator
\u2029
Paragraph Separator
Changed in version 3.2:
\v
and\f
added to list of line boundaries.For example:
>>> 'ab c\n\nde fg\rkl\r\n'.splitlines() ['ab c', '', 'de fg', 'kl'] >>> 'ab c\n\nde fg\rkl\r\n'.splitlines(keepends=True) ['ab c\n', '\n', 'de fg\r', 'kl\r\n']
Unlike
split()
when a delimiter string sep is given, this method returns an empty list for the empty string, and a terminal line break does not result in an extra line:>>> "".splitlines() [] >>> "One line\n".splitlines() ['One line']
For comparison,
split('\n')
gives:>>> ''.split('\n') [''] >>> 'Two lines\n'.split('\n') ['Two lines', '']
- str.startswith(prefix[, start[, end]])¶
Return
True
if string starts with the prefix, otherwise returnFalse
. prefix can also be a tuple of prefixes to look for. With optional start, test string beginning at that position. With optional end, stop comparing string at that position.
- str.strip([chars])¶
Return a copy of the string with the leading and trailing characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or
None
, the chars argument defaults to removing whitespace. The chars argument is not a prefix or suffix; rather, all combinations of its values are stripped:>>> ' spacious '.strip() 'spacious' >>> 'www.example.com'.strip('cmowz.') 'example'
The outermost leading and trailing chars argument values are stripped from the string. Characters are removed from the leading end until reaching a string character that is not contained in the set of characters in chars. A similar action takes place on the trailing end. For example:
>>> comment_string = '#....... Section 3.2.1 Issue #32 .......' >>> comment_string.strip('.#! ') 'Section 3.2.1 Issue #32'
- str.swapcase()¶
Return a copy of the string with uppercase characters converted to lowercase and vice versa. Note that it is not necessarily true that
s.swapcase().swapcase() == s
.
- str.title()¶
Return a titlecased version of the string where words start with an uppercase character and the remaining characters are lowercase.
For example:
>>> 'Hello world'.title() 'Hello World'
The algorithm uses a simple language-independent definition of a word as groups of consecutive letters. The definition works in many contexts but it means that apostrophes in contractions and possessives form word boundaries, which may not be the desired result:
>>> "they're bill's friends from the UK".title() "They'Re Bill'S Friends From The Uk"
The
string.capwords()
function does not have this problem, as it splits words on spaces only.Alternatively, a workaround for apostrophes can be constructed using regular expressions:
>>> import re >>> def titlecase(s): ... return re.sub(r"[A-Za-z]+('[A-Za-z]+)?", ... lambda mo: mo.group(0).capitalize(), ... s) ... >>> titlecase("they're bill's friends.") "They're Bill's Friends."
- str.translate(table)¶
Return a copy of the string in which each character has been mapped through the given translation table. The table must be an object that implements indexing via
__getitem__()
, typically a mapping or sequence. When indexed by a Unicode ordinal (an integer), the table object can do any of the following: return a Unicode ordinal or a string, to map the character to one or more other characters; returnNone
, to delete the character from the return string; or raise aLookupError
exception, to map the character to itself.You can use
str.maketrans()
to create a translation map from character-to-character mappings in different formats.See also the
codecs
module for a more flexible approach to custom character mappings.
- str.upper()¶
Return a copy of the string with all the cased characters [4] converted to uppercase. Note that
s.upper().isupper()
might beFalse
ifs
contains uncased characters or if the Unicode category of the resulting character(s) is not “Lu” (Letter, uppercase), but e.g. “Lt” (Letter, titlecase).The uppercasing algorithm used is described in section 3.13 ‘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 tolen(s)
.For example:
>>> "42".zfill(5) '00042' >>> "-42".zfill(5) '-0042'
printf
-style String Formatting¶
Note
The formatting operations described here exhibit a variety of quirks that
lead to a number of common errors (such as failing to display tuples and
dictionaries correctly). Using the newer formatted string literals, the str.format()
interface, or template strings may help avoid these errors. Each of these
alternatives provides their own trade-offs and benefits of simplicity,
flexibility, and/or extensibility.
String objects have one unique built-in operation: the %
operator (modulo).
This is also known as the string formatting or interpolation operator.
Given format % values
(where format is a string), %
conversion
specifications in format are replaced with zero or more elements of values.
The effect is similar to using the sprintf()
in the C language.
If format requires a single argument, values may be a single non-tuple object. [5] Otherwise, values must be a tuple with exactly the number of items specified by the format string, or a single mapping object (for example, a dictionary).
A conversion specifier contains two or more characters and has the following components, which must occur in this order:
The
'%'
character, which marks the start of the specifier.Mapping key (optional), consisting of a parenthesised sequence of characters (for example,
(somename)
).Conversion flags (optional), which affect the result of some conversion types.
Minimum field width (optional). If specified as an
'*'
(asterisk), the actual width is read from the next element of the tuple in values, and the object to convert comes after the minimum field width and optional precision.Precision (optional), given as a
'.'
(dot) followed by the precision. If specified as'*'
(an asterisk), the actual precision is read from the next element of the tuple in values, and the value to convert comes after the precision.Length modifier (optional).
Conversion type.
When the right argument is a dictionary (or other mapping type), then the
formats in the string must include a parenthesised mapping key into that
dictionary inserted immediately after the '%'
character. The mapping key
selects the value to be formatted from the mapping. For example:
>>> print('%(language)s has %(number)03d quote types.' %
... {'language': "Python", "number": 2})
Python has 002 quote types.
In this case no *
specifiers may occur in a format (since they require a
sequential parameter list).
The conversion flag characters are:
Flag |
Meaning |
---|---|
|
The value conversion will use the “alternate form” (where defined below). |
|
The conversion will be zero padded for numeric values. |
|
The converted value is left adjusted (overrides the |
|
(a space) A blank should be left before a positive number (or empty string) produced by a signed conversion. |
|
A sign character ( |
A length modifier (h
, l
, or L
) may be present, but is ignored as it
is not necessary for Python – so e.g. %ld
is identical to %d
.
The conversion types are:
Conversion |
Meaning |
Notes |
---|---|---|
|
Signed integer decimal. |
|
|
Signed integer decimal. |
|
|
Signed octal value. |
(1) |
|
Obsolete type – it is identical to |
(6) |
|
Signed hexadecimal (lowercase). |
(2) |
|
Signed hexadecimal (uppercase). |
(2) |
|
Floating-point exponential format (lowercase). |
(3) |
|
Floating-point exponential format (uppercase). |
(3) |
|
Floating-point decimal format. |
(3) |
|
Floating-point decimal format. |
(3) |
|
Floating-point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. |
(4) |
|
Floating-point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. |
(4) |
|
Single character (accepts integer or single character string). |
|
|
String (converts any Python object using
|
(5) |
|
String (converts any Python object using
|
(5) |
|
String (converts any Python object using
|
(5) |
|
No argument is converted, results in a |
Notes:
The alternate form causes a leading octal specifier (
'0o'
) to be inserted before the first digit.The alternate form causes a leading
'0x'
or'0X'
(depending on whether the'x'
or'X'
format was used) to be inserted before the first digit.The alternate form causes the result to always contain a decimal point, even if no digits follow it.
The precision determines the number of digits after the decimal point and defaults to 6.
The alternate form causes the result to always contain a decimal point, and trailing zeroes are not removed as they would otherwise be.
The precision determines the number of significant digits before and after the decimal point and defaults to 6.
If precision is
N
, the output is truncated toN
characters.See PEP 237.
Since Python strings have an explicit length, %s
conversions do not assume
that '\0'
is the end of the string.
Changed in version 3.1: %f
conversions for numbers whose absolute value is over 1e50 are no
longer replaced by %g
conversions.
Binary Sequence Types — bytes
, bytearray
, memoryview
¶
The core built-in types for manipulating binary data are bytes
and
bytearray
. They are supported by memoryview
which uses
the buffer protocol to access the memory of other
binary objects without needing to make a copy.
The array
module supports efficient storage of basic data types like
32-bit integers and IEEE754 double-precision floating values.
Bytes Objects¶
Bytes objects are immutable sequences of single bytes. Since many major binary protocols are based on the ASCII text encoding, bytes objects offer several methods that are only valid when working with ASCII compatible data and are closely related to string objects in a variety of other ways.
- class bytes([source[, encoding[, errors]]])¶
Firstly, the syntax for bytes literals is largely the same as that for string literals, except that a
b
prefix is added:Single quotes:
b'still allows embedded "double" quotes'
Double quotes:
b"still allows embedded 'single' quotes"
Triple quoted:
b'''3 single quotes'''
,b"""3 double quotes"""
Only ASCII characters are permitted in bytes literals (regardless of the declared source code encoding). Any binary values over 127 must be entered into bytes literals using the appropriate escape sequence.
As with string literals, bytes literals may also use a
r
prefix to disable processing of escape sequences. See String and Bytes literals for more about the various forms of bytes literal, including supported escape sequences.While bytes literals and representations are based on ASCII text, bytes objects actually behave like immutable sequences of integers, with each value in the sequence restricted such that
0 <= x < 256
(attempts to violate this restriction will triggerValueError
). This is done deliberately to emphasise that while many binary formats include ASCII based elements and can be usefully manipulated with some text-oriented algorithms, this is not generally the case for arbitrary binary data (blindly applying text processing algorithms to binary data formats that are not ASCII compatible will usually lead to data corruption).In addition to the literal forms, bytes objects can be created in a number of other ways:
A zero-filled bytes object of a specified length:
bytes(10)
From an iterable of integers:
bytes(range(20))
Copying existing binary data via the buffer protocol:
bytes(obj)
Also see the bytes built-in.
Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data. Accordingly, the bytes type has an additional class method to read data in that format:
- classmethod fromhex(string)¶
This
bytes
class method returns a bytes object, decoding the given string object. The string must contain two hexadecimal digits per byte, with ASCII whitespace being ignored.>>> bytes.fromhex('2Ef0 F1f2 ') b'.\xf0\xf1\xf2'
Changed in version 3.7:
bytes.fromhex()
now skips all ASCII whitespace in the string, not just spaces.
A reverse conversion function exists to transform a bytes object into its hexadecimal representation.
- hex([sep[, bytes_per_sep]])¶
Return a string object containing two hexadecimal digits for each byte in the instance.
>>> b'\xf0\xf1\xf2'.hex() 'f0f1f2'
If you want to make the hex string easier to read, you can specify a single character separator sep parameter to include in the output. By default, 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 = b'\xf0\xf1\xf2' >>> value.hex('-') 'f0-f1-f2' >>> value.hex('_', 2) 'f0_f1f2' >>> b'UUDDLRLRAB'.hex(' ', -4) '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, 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[, encoding[, errors]]])¶
There is no dedicated literal syntax for bytearray objects, instead they are always created by calling the constructor:
Creating an empty instance:
bytearray()
Creating a zero-filled instance with a given length:
bytearray(10)
From an iterable of integers:
bytearray(range(20))
Copying existing binary data via the buffer protocol:
bytearray(b'Hi!')
As bytearray objects are mutable, they support the mutable sequence operations in addition to the common bytes and bytearray operations described in Bytes and Bytearray Operations.
Also see the bytearray built-in.
Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data. Accordingly, the bytearray type has an additional class method to read data in that format:
- classmethod fromhex(string)¶
This
bytearray
class method returns bytearray object, decoding the given string object. The string must contain two hexadecimal digits per byte, with ASCII whitespace being ignored.>>> bytearray.fromhex('2Ef0 F1f2 ') bytearray(b'.\xf0\xf1\xf2')
Changed in version 3.7:
bytearray.fromhex()
now skips all ASCII whitespace in the string, not just spaces.
A reverse conversion function exists to transform a bytearray object into its hexadecimal representation.
- hex([sep[, bytes_per_sep]])¶
Return a string object containing two hexadecimal digits for each byte in the instance.
>>> bytearray(b'\xf0\xf1\xf2').hex() 'f0f1f2'
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.
Since bytearray objects are sequences of integers (akin to a list), for a
bytearray object b, b[0]
will be an integer, while b[0:1]
will be
a bytearray object of length 1. (This contrasts with text strings, where
both indexing and slicing will produce a string of length 1)
The representation of bytearray objects uses the bytes literal format
(bytearray(b'...')
) since it is often more useful than e.g.
bytearray([46, 46, 46])
. You can always convert a bytearray object into
a list of integers using list(b)
.
Bytes and Bytearray Operations¶
Both bytes and bytearray objects support the common sequence operations. They interoperate not just with operands of the same type, but with any bytes-like object. Due to this flexibility, they can be freely mixed in operations without causing errors. However, the return type of the result may depend on the order of operands.
Note
The methods on bytes and bytearray objects don’t accept strings as their arguments, just as the methods on strings don’t accept bytes as their arguments. For example, you have to write:
a = "abc"
b = a.replace("a", "f")
and:
a = b"abc"
b = a.replace(b"a", b"f")
Some bytes and bytearray operations assume the use of ASCII compatible binary formats, and hence should be avoided when working with arbitrary binary data. These restrictions are covered below.
Note
Using these ASCII based operations to manipulate binary data that is not stored in an ASCII based format may lead to data corruption.
The following methods on bytes and bytearray objects can be used with arbitrary binary data.
- bytes.count(sub[, start[, end]])¶
- bytearray.count(sub[, start[, end]])¶
Return the number of non-overlapping occurrences of subsequence sub in the range [start, end]. Optional arguments start and end are interpreted as in slice notation.
The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
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:>>> b'TestHook'.removeprefix(b'Test') b'Hook' >>> b'BaseTestCase'.removeprefix(b'Test') b'BaseTestCase'
The prefix may be any bytes-like object.
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
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:>>> b'MiscTests'.removesuffix(b'Tests') b'Misc' >>> b'TmpDirMixin'.removesuffix(b'Tests') b'TmpDirMixin'
The suffix may be any bytes-like object.
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
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), aUnicodeError
exception is raised. Other possible values are'ignore'
,'replace'
, and any other name registered viacodecs.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 temporarybytes
orbytearray
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 returnFalse
. suffix can also be a tuple of suffixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.The suffix(es) to search for may be any bytes-like object.
- bytes.find(sub[, start[, end]])¶
- bytearray.find(sub[, start[, end]])¶
Return the lowest index in the data where the subsequence sub is found, such that sub is contained in the slice
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
if sub is not found.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Note
The
find()
method should be used only if you need to know the position of sub. To check if sub is a substring or not, use thein
operator:>>> b'Py' in b'Python' True
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
- bytes.index(sub[, start[, end]])¶
- bytearray.index(sub[, start[, end]])¶
Like
find()
, but raiseValueError
when the subsequence is not found.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
- bytes.join(iterable)¶
- bytearray.join(iterable)¶
Return a bytes or bytearray object which is the concatenation of the binary data sequences in iterable. A
TypeError
will be raised if there are any values in iterable that are not bytes-like objects, includingstr
objects. The separator between elements is the contents of the bytes or bytearray object providing this method.
- static bytes.maketrans(from, to)¶
- static bytearray.maketrans(from, to)¶
This static method returns a translation table usable for
bytes.translate()
that will map each character in from into the character at the same position in to; from and to must both be bytes-like objects and have the same length.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])¶
- bytearray.replace(old, new[, count])¶
Return a copy of the sequence with all occurrences of subsequence old replaced by new. If the optional argument count is given, only the first count occurrences are replaced.
The subsequence to search for and its replacement may be any bytes-like object.
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.rfind(sub[, start[, end]])¶
- bytearray.rfind(sub[, start[, end]])¶
Return the highest index in the sequence where the subsequence sub is found, such that sub is contained within
s[start:end]
. Optional arguments start and end are interpreted as in slice notation. Return-1
on failure.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
- bytes.rindex(sub[, start[, end]])¶
- bytearray.rindex(sub[, start[, end]])¶
Like
rfind()
but raisesValueError
when the subsequence sub is not found.The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.
Changed in version 3.3: Also accept an integer in the range 0 to 255 as the subsequence.
- bytes.rpartition(sep)¶
- bytearray.rpartition(sep)¶
Split the sequence at the last occurrence of sep, and return a 3-tuple containing the part before the separator, the separator itself or its bytearray copy, and the part after the separator. If the separator is not found, return a 3-tuple containing two empty bytes or bytearray objects, followed by a copy of the original sequence.
The separator to search for may be any bytes-like object.
- bytes.startswith(prefix[, start[, end]])¶
- bytearray.startswith(prefix[, start[, end]])¶
Return
True
if the binary data starts with the specified prefix, otherwise returnFalse
. prefix can also be a tuple of prefixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.The prefix(es) to search for may be any bytes-like object.
- bytes.translate(table, /, delete=b'')¶
- bytearray.translate(table, /, delete=b'')¶
Return a copy of the bytes or bytearray object where all bytes occurring in the optional argument delete are removed, and the remaining bytes have been mapped through the given translation table, which must be a bytes object of length 256.
You can use the
bytes.maketrans()
method to create a translation table.Set the table argument to
None
for translations that only delete characters:>>> b'read this short text'.translate(None, b'aeiou') b'rd ths shrt txt'
Changed in version 3.6: delete is now supported as a keyword argument.
The following methods on bytes and bytearray objects have default behaviours that assume the use of ASCII compatible binary formats, but can still be used with arbitrary binary data by passing appropriate arguments. Note that all of the bytearray methods in this section do not operate in place, and instead produce new objects.
- bytes.center(width[, fillbyte])¶
- bytearray.center(width[, fillbyte])¶
Return a copy of the object centered in a sequence of length width. Padding is done using the specified fillbyte (default is an ASCII space). For
bytes
objects, the original sequence is returned if width is less than or equal tolen(s)
.Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.ljust(width[, fillbyte])¶
- bytearray.ljust(width[, fillbyte])¶
Return a copy of the object left justified in a sequence of length width. Padding is done using the specified fillbyte (default is an ASCII space). For
bytes
objects, the original sequence is returned if width is less than or equal tolen(s)
.Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.lstrip([chars])¶
- bytearray.lstrip([chars])¶
Return a copy of the sequence with specified leading bytes removed. The chars argument is a binary sequence specifying the set of byte values to be removed - the name refers to the fact this method is usually used with ASCII characters. If omitted or
None
, the chars argument defaults to removing ASCII whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped:>>> b' spacious '.lstrip() b'spacious ' >>> b'www.example.com'.lstrip(b'cmowz.') b'example.com'
The binary sequence of byte values to remove may be any bytes-like object. See
removeprefix()
for a method that will remove a single prefix string rather than all of a set of characters. For example:>>> b'Arthur: three!'.lstrip(b'Arthur: ') b'ee!' >>> b'Arthur: three!'.removeprefix(b'Arthur: ') b'three!'
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.rjust(width[, fillbyte])¶
- bytearray.rjust(width[, fillbyte])¶
Return a copy of the object right justified in a sequence of length width. Padding is done using the specified fillbyte (default is an ASCII space). For
bytes
objects, the original sequence is returned if width is less than or equal tolen(s)
.Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.rsplit(sep=None, maxsplit=-1)¶
- bytearray.rsplit(sep=None, maxsplit=-1)¶
Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done, the rightmost ones. If sep is not specified or
None
, any subsequence consisting solely of ASCII whitespace is a separator. Except for splitting from the right,rsplit()
behaves likesplit()
which is described in detail below.
- bytes.rstrip([chars])¶
- bytearray.rstrip([chars])¶
Return a copy of the sequence with specified trailing bytes removed. The chars argument is a binary sequence specifying the set of byte values to be removed - the name refers to the fact this method is usually used with ASCII characters. If omitted or
None
, the chars argument defaults to removing ASCII whitespace. The chars argument is not a suffix; rather, all combinations of its values are stripped:>>> b' spacious '.rstrip() b' spacious' >>> b'mississippi'.rstrip(b'ipz') b'mississ'
The binary sequence of byte values to remove may be any bytes-like object. See
removesuffix()
for a method that will remove a single suffix string rather than all of a set of characters. For example:>>> b'Monty Python'.rstrip(b' Python') b'M' >>> b'Monty Python'.removesuffix(b' Python') b'Monty'
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.split(sep=None, maxsplit=-1)¶
- bytearray.split(sep=None, maxsplit=-1)¶
Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given and non-negative, at most maxsplit splits are done (thus, the list will have at most
maxsplit+1
elements). If maxsplit is not specified or is-1
, then there is no limit on the number of splits (all possible splits are made).If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty subsequences (for example,
b'1,,2'.split(b',')
returns[b'1', b'', b'2']
). The sep argument may consist of a multibyte sequence 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:
>>> b'1,2,3'.split(b',') [b'1', b'2', b'3'] >>> b'1,2,3'.split(b',', maxsplit=1) [b'1', b'2,3'] >>> b'1,2,,3,'.split(b',') [b'1', b'2', b'', b'3', b''] >>> b'1<>2<>3<4'.split(b'<>') [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:
>>> b'1 2 3'.split() [b'1', b'2', b'3'] >>> b'1 2 3'.split(maxsplit=1) [b'1', b'2 3'] >>> b' 1 2 3 '.split() [b'1', b'2', b'3']
- bytes.strip([chars])¶
- bytearray.strip([chars])¶
Return a copy of the sequence with specified leading and trailing bytes removed. The chars argument is a binary sequence specifying the set of byte values to be removed - the name refers to the fact this method is usually used with ASCII characters. If omitted or
None
, the chars argument defaults to removing ASCII whitespace. The chars argument is not a prefix or suffix; rather, all combinations of its values are stripped:>>> b' spacious '.strip() b'spacious' >>> b'www.example.com'.strip(b'cmowz.') b'example'
The binary sequence of byte values to remove may be any bytes-like object.
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
The following methods on bytes and bytearray objects assume the use of ASCII compatible binary formats and should not be applied to arbitrary binary data. Note that all of the bytearray methods in this section do not operate in place, and instead produce new objects.
- bytes.capitalize()¶
- bytearray.capitalize()¶
Return a copy of the sequence with each byte interpreted as an ASCII character, and the first byte capitalized and the rest lowercased. Non-ASCII byte values are passed through unchanged.
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.expandtabs(tabsize=8)¶
- bytearray.expandtabs(tabsize=8)¶
Return a copy of the sequence where all ASCII tab characters are replaced by one or more ASCII spaces, depending on the current column and the given tab size. Tab positions occur every tabsize bytes (default is 8, giving tab positions at columns 0, 8, 16 and so on). To expand the sequence, the current column is set to zero and the sequence is examined byte by byte. If the byte is an ASCII tab character (
b'\t'
), one or more space characters are inserted in the result until the current column is equal to the next tab position. (The tab character itself is not copied.) If the current byte is an ASCII newline (b'\n'
) or carriage return (b'\r'
), it is copied and the current column is reset to zero. Any other byte value is copied unchanged and the current column is incremented by one regardless of how the byte value is represented when printed:>>> b'01\t012\t0123\t01234'.expandtabs() b'01 012 0123 01234' >>> b'01\t012\t0123\t01234'.expandtabs(4) b'01 012 0123 01234'
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.isalnum()¶
- bytearray.isalnum()¶
Return
True
if all bytes in the sequence are alphabetical ASCII characters or ASCII decimal digits and the sequence is not empty,False
otherwise. Alphabetic ASCII characters are those byte values in the sequenceb'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
. ASCII decimal digits are those byte values in the sequenceb'0123456789'
.For example:
>>> b'ABCabc1'.isalnum() True >>> b'ABC abc1'.isalnum() False
- bytes.isalpha()¶
- bytearray.isalpha()¶
Return
True
if all bytes in the sequence are alphabetic ASCII characters and the sequence is not empty,False
otherwise. Alphabetic ASCII characters are those byte values in the sequenceb'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
.For example:
>>> b'ABCabc'.isalpha() True >>> b'ABCabc1'.isalpha() False
- bytes.isascii()¶
- bytearray.isascii()¶
Return
True
if the sequence is empty or all bytes in the sequence are ASCII,False
otherwise. ASCII bytes are in the range 0-0x7F.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 sequenceb'0123456789'
.For example:
>>> b'1234'.isdigit() True >>> b'1.23'.isdigit() False
- bytes.islower()¶
- bytearray.islower()¶
Return
True
if there is at least one lowercase ASCII character in the sequence and no uppercase ASCII characters,False
otherwise.For example:
>>> b'hello world'.islower() True >>> b'Hello world'.islower() False
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.
- bytes.isspace()¶
- bytearray.isspace()¶
Return
True
if all bytes in the sequence are ASCII whitespace and the sequence is not empty,False
otherwise. ASCII whitespace characters are those byte values in the sequenceb' \t\n\r\x0b\f'
(space, tab, newline, carriage return, vertical tab, form feed).
- bytes.istitle()¶
- bytearray.istitle()¶
Return
True
if the sequence is ASCII titlecase and the sequence is not empty,False
otherwise. Seebytes.title()
for more details on the definition of “titlecase”.For example:
>>> b'Hello World'.istitle() True >>> b'Hello world'.istitle() False
- bytes.isupper()¶
- bytearray.isupper()¶
Return
True
if there is at least one uppercase alphabetic ASCII character in the sequence and no lowercase ASCII characters,False
otherwise.For example:
>>> b'HELLO WORLD'.isupper() True >>> b'Hello world'.isupper() False
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.
- bytes.lower()¶
- bytearray.lower()¶
Return a copy of the sequence with all the uppercase ASCII characters converted to their corresponding lowercase counterpart.
For example:
>>> b'Hello World'.lower() b'hello world'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.splitlines(keepends=False)¶
- bytearray.splitlines(keepends=False)¶
Return a list of the lines in the binary sequence, breaking at ASCII line boundaries. This method uses the universal newlines approach to splitting lines. Line breaks are not included in the resulting list unless keepends is given and true.
For example:
>>> b'ab c\n\nde fg\rkl\r\n'.splitlines() [b'ab c', b'', b'de fg', b'kl'] >>> b'ab c\n\nde fg\rkl\r\n'.splitlines(keepends=True) [b'ab c\n', b'\n', b'de fg\r', b'kl\r\n']
Unlike
split()
when a delimiter string sep is given, this method returns an empty list for the empty string, and a terminal line break does not result in an extra line:>>> b"".split(b'\n'), b"Two lines\n".split(b'\n') ([b''], [b'Two lines', b'']) >>> b"".splitlines(), b"One line\n".splitlines() ([], [b'One line'])
- bytes.swapcase()¶
- bytearray.swapcase()¶
Return a copy of the sequence with all the lowercase ASCII characters converted to their corresponding uppercase counterpart and vice-versa.
For example:
>>> b'Hello World'.swapcase() b'hELLO wORLD'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.Unlike
str.swapcase()
, it is always the case thatbin.swapcase().swapcase() == bin
for the binary versions. Case conversions are symmetrical in ASCII, even though that is not generally true for arbitrary Unicode code points.Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.title()¶
- bytearray.title()¶
Return a titlecased version of the binary sequence where words start with an uppercase ASCII character and the remaining characters are lowercase. Uncased byte values are left unmodified.
For example:
>>> b'Hello world'.title() b'Hello World'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
. All other byte values are uncased.The algorithm uses a simple language-independent definition of a word as groups of consecutive letters. The definition works in many contexts but it means that apostrophes in contractions and possessives form word boundaries, which may not be the desired result:
>>> b"they're bill's friends from the UK".title() b"They'Re Bill'S Friends From The Uk"
A workaround for apostrophes can be constructed using regular expressions:
>>> import re >>> def titlecase(s): ... return re.sub(rb"[A-Za-z]+('[A-Za-z]+)?", ... lambda mo: mo.group(0)[0:1].upper() + ... mo.group(0)[1:].lower(), ... s) ... >>> titlecase(b"they're bill's friends.") b"They're Bill's Friends."
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.upper()¶
- bytearray.upper()¶
Return a copy of the sequence with all the lowercase ASCII characters converted to their corresponding uppercase counterpart.
For example:
>>> b'Hello World'.upper() b'HELLO WORLD'
Lowercase ASCII characters are those byte values in the sequence
b'abcdefghijklmnopqrstuvwxyz'
. Uppercase ASCII characters are those byte values in the sequenceb'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
.Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
- bytes.zfill(width)¶
- bytearray.zfill(width)¶
Return a copy of the sequence left filled with ASCII
b'0'
digits to make a sequence of length width. A leading sign prefix (b'+'
/b'-'
) is handled by inserting the padding after the sign character rather than before. Forbytes
objects, the original sequence is returned if width is less than or equal tolen(seq)
.For example:
>>> b"42".zfill(5) b'00042' >>> b"-42".zfill(5) b'-0042'
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
printf
-style Bytes Formatting¶
Note
The formatting operations described here exhibit a variety of quirks that lead to a number of common errors (such as failing to display tuples and dictionaries correctly). If the value being printed may be a tuple or dictionary, wrap it in a tuple.
Bytes objects (bytes
/bytearray
) have one unique built-in operation:
the %
operator (modulo).
This is also known as the bytes formatting or interpolation operator.
Given format % values
(where format is a bytes object), %
conversion
specifications in format are replaced with zero or more elements of values.
The effect is similar to using the sprintf()
in the C language.
If format requires a single argument, values may be a single non-tuple object. [5] Otherwise, values must be a tuple with exactly the number of items specified by the format bytes object, or a single mapping object (for example, a dictionary).
A conversion specifier contains two or more characters and has the following components, which must occur in this order:
The
'%'
character, which marks the start of the specifier.Mapping key (optional), consisting of a parenthesised sequence of characters (for example,
(somename)
).Conversion flags (optional), which affect the result of some conversion types.
Minimum field width (optional). If specified as an
'*'
(asterisk), the actual width is read from the next element of the tuple in values, and the object to convert comes after the minimum field width and optional precision.Precision (optional), given as a
'.'
(dot) followed by the precision. If specified as'*'
(an asterisk), the actual precision is read from the next element of the tuple in values, and the value to convert comes after the precision.Length modifier (optional).
Conversion type.
When the right argument is a dictionary (or other mapping type), then the
formats in the bytes object must include a parenthesised mapping key into that
dictionary inserted immediately after the '%'
character. The mapping key
selects the value to be formatted from the mapping. For example:
>>> print(b'%(language)s has %(number)03d quote types.' %
... {b'language': b"Python", b"number": 2})
b'Python has 002 quote types.'
In this case no *
specifiers may occur in a format (since they require a
sequential parameter list).
The conversion flag characters are:
Flag |
Meaning |
---|---|
|
The value conversion will use the “alternate form” (where defined below). |
|
The conversion will be zero padded for numeric values. |
|
The converted value is left adjusted (overrides the |
|
(a space) A blank should be left before a positive number (or empty string) produced by a signed conversion. |
|
A sign character ( |
A length modifier (h
, l
, or L
) may be present, but is ignored as it
is not necessary for Python – so e.g. %ld
is identical to %d
.
The conversion types are:
Conversion |
Meaning |
Notes |
---|---|---|
|
Signed integer decimal. |
|
|
Signed integer decimal. |
|
|
Signed octal value. |
(1) |
|
Obsolete type – it is identical to |
(8) |
|
Signed hexadecimal (lowercase). |
(2) |
|
Signed hexadecimal (uppercase). |
(2) |
|
Floating-point exponential format (lowercase). |
(3) |
|
Floating-point exponential format (uppercase). |
(3) |
|
Floating-point decimal format. |
(3) |
|
Floating-point decimal format. |
(3) |
|
Floating-point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. |
(4) |
|
Floating-point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. |
(4) |
|
Single byte (accepts integer or single byte objects). |
|
|
Bytes (any object that follows the
buffer protocol or has
|
(5) |
|
|
(6) |
|
Bytes (converts any Python object using
|
(5) |
|
|
(7) |
|
No argument is converted, results in a |
Notes:
The alternate form causes a leading octal specifier (
'0o'
) to be inserted before the first digit.The alternate form causes a leading
'0x'
or'0X'
(depending on whether the'x'
or'X'
format was used) to be inserted before the first digit.The alternate form causes the result to always contain a decimal point, even if no digits follow it.
The precision determines the number of digits after the decimal point and defaults to 6.
The alternate form causes the result to always contain a decimal point, and trailing zeroes are not removed as they would otherwise be.
The precision determines the number of significant digits before and after the decimal point and defaults to 6.
If precision is
N
, the output is truncated toN
characters.b'%s'
is deprecated, but will not be removed during the 3.x series.b'%r'
is deprecated, but will not be removed during the 3.x series.See PEP 237.
Note
The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.
See also
PEP 461 - Adding % formatting to bytes and bytearray
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 includebytes
andbytearray
.A
memoryview
has the notion of an element, which is the atomic memory unit handled by the originating object. For many simple types such asbytes
andbytearray
, an element is a single byte, but other types such asarray.array
may have bigger elements.len(view)
is equal to the length oftolist
, which is the nested list representation of the view. Ifview.ndim = 1
, this is equal to the number of elements in the view.Changed in version 3.12: If
view.ndim == 0
,len(view)
now raisesTypeError
instead of returning 1.The
itemsize
attribute will give you the number of bytes in a single element.A
memoryview
supports slicing and indexing to expose its data. One-dimensional slicing will result in a subview:>>> v = memoryview(b'abcefg') >>> v[1] 98 >>> v[-1] 103 >>> v[1:4] <memory at 0x7f3ddc9f4350> >>> bytes(v[1:4]) b'bce'
If
format
is one of the native format specifiers from thestruct
module, indexing with an integer or a tuple of integers is also supported and returns a single element with the correct type. One-dimensional memoryviews can be indexed with an integer or a one-integer tuple. Multi-dimensional memoryviews can be indexed with tuples of exactly ndim integers where ndim is the number of dimensions. Zero-dimensional memoryviews can be indexed with the empty tuple.Here is an example with a non-byte format:
>>> import array >>> a = array.array('l', [-11111111, 22222222, -33333333, 44444444]) >>> m = memoryview(a) >>> m[0] -11111111 >>> m[-1] 44444444 >>> m[::2].tolist() [-11111111, -33333333]
If the underlying object is writable, the memoryview supports one-dimensional slice assignment. Resizing is not allowed:
>>> data = bytearray(b'abcefg') >>> v = memoryview(data) >>> v.readonly False >>> v[0] = ord(b'z') >>> data bytearray(b'zbcefg') >>> v[1:4] = b'123' >>> data bytearray(b'z123fg') >>> v[2:3] = b'spam' Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: memoryview assignment: lvalue and rvalue have different structures >>> v[2:6] = b'spam' >>> data bytearray(b'z1spam')
One-dimensional memoryviews of hashable (read-only) types with formats ‘B’, ‘b’ or ‘c’ are also hashable. The hash is defined as
hash(m) == hash(m.tobytes())
:>>> v = memoryview(b'abcefg') >>> hash(v) == hash(b'abcefg') True >>> hash(v[2:4]) == hash(b'ce') True >>> hash(v[::-2]) == hash(b'abcefg'[::-2]) True
Changed in version 3.3: One-dimensional memoryviews can now be sliced. One-dimensional memoryviews with formats ‘B’, ‘b’ or ‘c’ are now hashable.
Changed in version 3.4: memoryview is now registered automatically with
collections.abc.Sequence
Changed in version 3.5: memoryviews can now be indexed with tuple of integers.
memoryview
has several methods:- __eq__(exporter)¶
A memoryview and a PEP 3118 exporter are equal if their shapes are equivalent and if all corresponding values are equal when the operands’ respective format codes are interpreted using
struct
syntax.For the subset of
struct
format strings currently supported bytolist()
,v
andw
are equal ifv.tolist() == w.tolist()
:>>> import array >>> a = array.array('I', [1, 2, 3, 4, 5]) >>> b = array.array('d', [1.0, 2.0, 3.0, 4.0, 5.0]) >>> c = array.array('b', [5, 3, 1]) >>> x = memoryview(a) >>> y = memoryview(b) >>> x == a == y == b True >>> x.tolist() == a.tolist() == y.tolist() == b.tolist() True >>> z = y[::-2] >>> z == c True >>> z.tolist() == c.tolist() True
If either format string is not supported by the
struct
module, then the objects will always compare as unequal (even if the format strings and buffer contents are identical):>>> from ctypes import BigEndianStructure, c_long >>> class BEPoint(BigEndianStructure): ... _fields_ = [("x", c_long), ("y", c_long)] ... >>> point = BEPoint(100, 200) >>> a = memoryview(point) >>> b = memoryview(point) >>> a == point False >>> a == b False
Note that, as with floating-point numbers,
v is w
does not implyv == w
for memoryview objects.Changed in version 3.3: Previous versions compared the raw memory disregarding the item format and the logical array structure.
- tobytes(order='C')¶
Return the data in the buffer as a bytestring. This is equivalent to calling the
bytes
constructor on the memoryview.>>> m = memoryview(b"abc") >>> m.tobytes() b'abc' >>> bytes(m) b'abc'
For non-contiguous arrays the result is equal to the flattened list representation with all elements converted to bytes.
tobytes()
supports all format strings, including those that are not instruct
module syntax.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([sep[, bytes_per_sep]])¶
Return a string object containing two hexadecimal digits for each byte in the buffer.
>>> m = memoryview(b"abc") >>> m.hex() '616263'
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(b'abc').tolist() [97, 98, 99] >>> import array >>> a = array.array('d', [1.1, 2.2, 3.3]) >>> m = memoryview(a) >>> m.tolist() [1.1, 2.2, 3.3]
- toreadonly()¶
Return a readonly version of the memoryview object. The original memoryview object is unchanged.
>>> m = memoryview(bytearray(b'abc')) >>> mm = m.toreadonly() >>> mm.tolist() [97, 98, 99] >>> mm[0] = 42 Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: cannot modify read-only memory >>> m[0] = 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, a
bytearray
would temporarily forbid resizing); therefore, calling release() is handy to remove these restrictions (and free any dangling resources) as soon as possible.After this method has been called, any further operation on the view raises a
ValueError
(exceptrelease()
itself which can be called multiple times):>>> m = memoryview(b'abc') >>> m.release() >>> m[0] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: operation forbidden on released memoryview object
The context management protocol can be used for a similar effect, using the
with
statement:>>> with memoryview(b'abc') as m: ... m[0] ... 97 >>> m[0] Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: operation forbidden on released memoryview object
Added in version 3.2.
- cast(format[, shape])¶
Cast a memoryview to a new format or shape. shape defaults to
[byte_length//new_itemsize]
, which means that the result view will be one-dimensional. The return value is a new memoryview, but the buffer itself is not copied. Supported casts are 1D -> C-contiguous and C-contiguous -> 1D.The destination format is restricted to a single element native format in
struct
syntax. One of the formats must be a byte format (‘B’, ‘b’ or ‘c’). The byte length of the result must be the same as the original length. Note that all byte lengths may depend on the operating system.Cast 1D/long to 1D/unsigned bytes:
>>> import array >>> a = array.array('l', [1,2,3]) >>> x = memoryview(a) >>> x.format 'l' >>> x.itemsize 8 >>> len(x) 3 >>> x.nbytes 24 >>> y = x.cast('B') >>> y.format 'B' >>> y.itemsize 1 >>> len(y) 24 >>> y.nbytes 24
Cast 1D/unsigned bytes to 1D/char:
>>> b = bytearray(b'zyz') >>> x = memoryview(b) >>> x[0] = b'a' Traceback (most recent call last): ... TypeError: memoryview: invalid type for format 'B' >>> y = x.cast('c') >>> y[0] = b'a' >>> b bytearray(b'ayz')
Cast 1D/bytes to 3D/ints to 1D/signed char:
>>> import struct >>> buf = struct.pack("i"*12, *list(range(12))) >>> x = memoryview(buf) >>> y = x.cast('i', shape=[2,2,3]) >>> y.tolist() [[[0, 1, 2], [3, 4, 5]], [[6, 7, 8], [9, 10, 11]]] >>> y.format 'i' >>> y.itemsize 4 >>> len(y) 2 >>> y.nbytes 48 >>> z = y.cast('b') >>> z.format 'b' >>> z.itemsize 1 >>> len(z) 48 >>> z.nbytes 48
Cast 1D/unsigned long to 2D/unsigned long:
>>> buf = struct.pack("L"*6, *list(range(6))) >>> x = memoryview(buf) >>> y = x.cast('L', shape=[2,3]) >>> len(y) 2 >>> y.nbytes 48 >>> y.tolist() [[0, 1, 2], [3, 4, 5]]
Added in version 3.3.
Changed in version 3.5: The source format is no longer restricted when casting to a byte view.
There are also several readonly attributes available:
- obj¶
The underlying object of the memoryview:
>>> b = bytearray(b'xyz') >>> m = memoryview(b) >>> m.obj is b True
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 tolen(m)
:>>> import array >>> a = array.array('i', [1,2,3,4,5]) >>> m = memoryview(a) >>> len(m) 5 >>> m.nbytes 20 >>> y = m[::2] >>> len(y) 3 >>> y.nbytes 12 >>> len(y.tobytes()) 12
Multi-dimensional arrays:
>>> import struct >>> buf = struct.pack("d"*12, *[1.5*x for x in range(12)]) >>> x = memoryview(buf) >>> y = x.cast('d', shape=[3,4]) >>> y.tolist() [[0.0, 1.5, 3.0, 4.5], [6.0, 7.5, 9.0, 10.5], [12.0, 13.5, 15.0, 16.5]] >>> len(y) 3 >>> y.nbytes 96
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 thatmemoryview(b'abc')[0] == b'abc'[0] == 97
.
- itemsize¶
The size in bytes of each element of the memoryview:
>>> import array, struct >>> m = memoryview(array.array('H', [32000, 32001, 32002])) >>> m.itemsize 2 >>> m[0] 32000 >>> struct.calcsize('H') == m.itemsize True
- ndim¶
An integer indicating how many dimensions of a multi-dimensional array the memory represents.
- shape¶
A tuple of integers the length of
ndim
giving the shape of the memory as an N-dimensional array.Changed in version 3.3: An empty tuple instead of
None
when ndim = 0.
- strides¶
A tuple of integers the length of
ndim
giving the size in bytes to access each element for each dimension of the array.Changed in version 3.3: An empty tuple instead of
None
when ndim = 0.
- suboffsets¶
Used internally for PIL-style arrays. The value is informational only.
- c_contiguous¶
A bool indicating whether the memory is C-contiguous.
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.
Set Types — set
, frozenset
¶
A set object is an unordered collection of distinct hashable objects.
Common uses include membership testing, removing duplicates from a sequence, and
computing mathematical operations such as intersection, union, difference, and
symmetric difference.
(For other containers see the built-in dict
, list
,
and tuple
classes, and the collections
module.)
Like other collections, sets support x in set
, len(set)
, and for x in
set
. Being an unordered collection, sets do not record element position or
order of insertion. Accordingly, sets do not support indexing, slicing, or
other sequence-like behavior.
There are currently two built-in set types, set
and frozenset
.
The set
type is mutable — the contents can be changed using methods
like add()
and remove()
. Since it is mutable, it has no
hash value and cannot be used as either a dictionary key or as an element of
another set. The frozenset
type is immutable and hashable —
its contents cannot be altered after it is created; it can therefore be used as
a dictionary key or as an element of another set.
Non-empty sets (not frozensets) can be created by placing a comma-separated list
of elements within braces, for example: {'jack', 'sjoerd'}
, in addition to the
set
constructor.
The constructors for both classes work the same:
- class set([iterable])¶
- class frozenset([iterable])¶
Return a new set or frozenset object whose elements are taken from iterable. The elements of a set must be hashable. To represent sets of sets, the inner sets must be
frozenset
objects. If iterable is not specified, a new empty set is returned.Sets can be created by several means:
Use a comma-separated list of elements within braces:
{'jack', 'sjoerd'}
Use a set comprehension:
{c for c in 'abracadabra' if c not in 'abc'}
Use the type constructor:
set()
,set('foobar')
,set(['a', 'b', 'foo'])
Instances of
set
andfrozenset
provide the following operations:- len(s)
Return the number of elements in set s (cardinality of s).
- x in s
Test x for membership in s.
- x not in s
Test x for non-membership in s.
- isdisjoint(other)¶
Return
True
if the set has no elements in common with other. Sets are disjoint if and only if their intersection is the empty set.
- issubset(other)¶
- set <= other
Test whether every element in the set is in other.
- set < other
Test whether the set is a proper subset of other, that is,
set <= other and set != other
.
- issuperset(other)¶
- set >= other
Test whether every element in other is in the set.
- set > other
Test whether the set is a proper superset of other, that is,
set >= other and set != other
.
- union(*others)¶
- set | other | ...
Return a new set with elements from the set and all others.
- intersection(*others)¶
- set & other & ...
Return a new set with elements common to the set and all others.
- difference(*others)¶
- set - other - ...
Return a new set with elements in the set that are not in the others.
- symmetric_difference(other)¶
- set ^ other
Return a new set with elements in either the set or other but not both.
- copy()¶
Return a shallow copy of the set.
Note, the non-operator versions of
union()
,intersection()
,difference()
,symmetric_difference()
,issubset()
, andissuperset()
methods will accept any iterable as an argument. In contrast, their operator based counterparts require their arguments to be sets. This precludes error-prone constructions likeset('abc') & 'cbs'
in favor of the more readableset('abc').intersection('cbs')
.Both
set
andfrozenset
support set to set comparisons. Two sets are equal if and only if every element of each set is contained in the other (each is a subset of the other). A set is less than another set if and only if the first set is a proper subset of the second set (is a subset, but is not equal). A set is greater than another set if and only if the first set is a proper superset of the second set (is a superset, but is not equal).Instances of
set
are compared to instances offrozenset
based on their members. For example,set('abc') == frozenset('abc')
returnsTrue
and so doesset('abc') in set([frozenset('abc')])
.The subset and equality comparisons do not generalize to a total ordering function. For example, any two nonempty disjoint sets are not equal and are not subsets of each other, so all of the following return
False
:a<b
,a==b
, ora>b
.Since sets only define partial ordering (subset relationships), the output of the
list.sort()
method is undefined for lists of sets.Set elements, like dictionary keys, must be hashable.
Binary operations that mix
set
instances withfrozenset
return the type of the first operand. For example:frozenset('ab') | set('bc')
returns an instance offrozenset
.The following table lists operations available for
set
that do not apply to immutable instances offrozenset
:- update(*others)¶
- set |= other | ...
Update the set, adding elements from all others.
- intersection_update(*others)¶
- set &= other & ...
Update the set, keeping only elements found in it and all others.
- difference_update(*others)¶
- set -= other | ...
Update the set, removing elements found in others.
- symmetric_difference_update(other)¶
- set ^= other
Update the set, keeping only elements found in either set, but not in both.
- add(elem)¶
Add element elem to the set.
- remove(elem)¶
Remove element elem from the set. Raises
KeyError
if elem is not contained in the set.
- discard(elem)¶
Remove element elem from the set if it is present.
- clear()¶
Remove all elements from the set.
Note, the non-operator versions of the
update()
,intersection_update()
,difference_update()
, andsymmetric_difference_update()
methods will accept any iterable as an argument.Note, the elem argument to the
__contains__()
,remove()
, anddiscard()
methods may be a set. To support searching for an equivalent frozenset, a temporary one is created from elem.
Mapping Types — dict
¶
A mapping object maps hashable values to arbitrary objects.
Mappings are mutable objects. There is currently only one standard mapping
type, the dictionary. (For other containers see the built-in
list
, set
, and tuple
classes, and the
collections
module.)
A dictionary’s keys are almost arbitrary values. Values that are not
hashable, that is, values containing lists, dictionaries or other
mutable types (that are compared by value rather than by object identity) may
not be used as keys.
Values that compare equal (such as 1
, 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: x ** 2 for x in range(10)}
Use the type constructor:
dict()
,dict([('foo', 100), ('bar', 200)])
,dict(foo=100, bar=200)
If no positional argument is given, an empty dictionary is created. If a positional argument is given and it is a mapping object, a dictionary is created with the same key-value pairs as the mapping object. Otherwise, the positional argument must be an iterable object. Each item in the iterable must itself be an iterable with exactly two objects. The first object of each item becomes a key in the new dictionary, and the second object the corresponding value. If a key occurs more than once, the last value for that key becomes the corresponding value in the new dictionary.
If keyword arguments are given, the keyword arguments and their values are added to the dictionary created from the positional argument. If a key being added is already present, the value from the keyword argument replaces the value from the positional argument.
To illustrate, the following examples all return a dictionary equal to
{"one": 1, "two": 2, "three": 3}
:>>> a = dict(one=1, two=2, three=3) >>> b = {'one': 1, 'two': 2, 'three': 3} >>> c = dict(zip(['one', 'two', 'three'], [1, 2, 3])) >>> d = dict([('two', 2), ('one', 1), ('three', 3)]) >>> e = dict({'three': 3, 'one': 1, 'two': 2}) >>> f = dict({'one': 1, 'three': 3}, two=2) >>> a == b == c == d == e == f True
Providing keyword arguments as in the first example only works for keys that are valid Python identifiers. Otherwise, any valid keys can be used.
These are the operations that dictionaries support (and therefore, custom mapping types should support too):
- list(d)
Return a list of all the keys used in the dictionary d.
- len(d)
Return the number of items in the dictionary d.
- d[key]
Return the item of d with key key. Raises a
KeyError
if key is not in the map.If a subclass of dict defines a method
__missing__()
and key is not present, thed[key]
operation calls that method with the key key as argument. Thed[key]
operation then returns or raises whatever is returned or raised by the__missing__(key)
call. No other operations or methods invoke__missing__()
. If__missing__()
is not defined,KeyError
is raised.__missing__()
must be a method; it cannot be an instance variable:>>> class Counter(dict): ... def __missing__(self, key): ... return 0 ... >>> c = Counter() >>> c['red'] 0 >>> c['red'] += 1 >>> c['red'] 1
The example above shows part of the implementation of
collections.Counter
. A different__missing__
method is used bycollections.defaultdict
.
- d[key] = value
Set
d[key]
to value.
- del d[key]
Remove
d[key]
from d. Raises aKeyError
if key is not in the map.
- key in d
Return
True
if d has a key key, elseFalse
.
- key not in d
Equivalent to
not key in d
.
- iter(d)
Return an iterator over the keys of the dictionary. This is a shortcut for
iter(d.keys())
.
- clear()¶
Remove all items from the dictionary.
- copy()¶
Return a shallow copy of the dictionary.
- classmethod fromkeys(iterable, value=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 toNone
. All of the values refer to just a single instance, so it generally doesn’t make sense for value to be a mutable object such as an empty list. To get distinct values, use a dict comprehension instead.
- get(key, default=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 aKeyError
.
- items()¶
Return a new view of the dictionary’s items (
(key, value)
pairs). See the documentation of view objects.
- keys()¶
Return a new view of the dictionary’s keys. See the documentation of view objects.
- pop(key[, default])¶
If key is in the dictionary, remove it and return its value, else return default. If default is not given and key is not in the dictionary, a
KeyError
is raised.
- popitem()¶
Remove and return a
(key, value)
pair from the dictionary. Pairs are returned in LIFO order.popitem()
is useful to destructively iterate over a dictionary, as often used in set algorithms. If the dictionary is empty, callingpopitem()
raises aKeyError
.Changed in version 3.7: LIFO order is now guaranteed. In prior versions,
popitem()
would return an arbitrary key/value pair.
- reversed(d)
Return a reverse iterator over the keys of the dictionary. This is a shortcut for
reversed(d.keys())
.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([other])¶
Update the dictionary with the key/value pairs from other, overwriting existing keys. Return
None
.update()
accepts either another dictionary object or an iterable of key/value pairs (as tuples or other iterables of length two). If keyword arguments are specified, the dictionary is then updated with those key/value pairs:d.update(red=1, blue=2)
.
- values()¶
Return a new view of the dictionary’s values. See the documentation of view objects.
An equality comparison between one
dict.values()
view and another will always returnFalse
. This also applies when comparingdict.values()
to itself:>>> d = {'a': 1} >>> d.values() == d.values() False
- d | other
Create a new dictionary with the merged keys and values of d and other, which must both be dictionaries. The values of other take priority when d and other share keys.
Added in version 3.9.
- d |= other
Update the dictionary d with keys and values from other, which may be either a mapping or an iterable of key/value pairs. The values of other take priority when d and other share keys.
Added in version 3.9.
Dictionaries compare equal if and only if they have the same
(key, value)
pairs (regardless of ordering). Order comparisons (‘<’, ‘<=’, ‘>=’, ‘>’) raiseTypeError
.Dictionaries preserve insertion order. Note that updating a key does not affect the order. Keys added after deletion are inserted at the end.
>>> d = {"one": 1, "two": 2, "three": 3, "four": 4} >>> d {'one': 1, 'two': 2, 'three': 3, 'four': 4} >>> list(d) ['one', 'two', 'three', 'four'] >>> list(d.values()) [1, 2, 3, 4] >>> d["one"] = 42 >>> d {'one': 42, 'two': 2, 'three': 3, 'four': 4} >>> del d["two"] >>> d["two"] = None >>> d {'one': 42, 'three': 3, 'four': 4, 'two': None}
Changed in version 3.7: Dictionary order is guaranteed to be insertion order. This behavior was an implementation detail of CPython from 3.6.
Dictionaries and dictionary views are reversible.
>>> d = {"one": 1, "two": 2, "three": 3, "four": 4} >>> d {'one': 1, 'two': 2, 'three': 3, 'four': 4} >>> list(reversed(d)) ['four', 'three', 'two', 'one'] >>> list(reversed(d.values())) [4, 3, 2, 1] >>> list(reversed(d.items())) [('four', 4), ('three', 3), ('two', 2), ('one', 1)]
Changed in version 3.8: Dictionaries are now reversible.
See also
types.MappingProxyType
can be used to create a read-only view
of a dict
.
Dictionary view objects¶
The objects returned by dict.keys()
, dict.values()
and
dict.items()
are view objects. They provide a dynamic view on the
dictionary’s entries, which means that when the dictionary changes, the view
reflects these changes.
Dictionary views can be iterated over to yield their respective data, and support membership tests:
- len(dictview)
Return the number of entries in the dictionary.
- iter(dictview)
Return an iterator over the keys, values or items (represented as tuples of
(key, value)
) in the dictionary.Keys and values are iterated over in insertion order. This allows the creation of
(value, key)
pairs usingzip()
:pairs = zip(d.values(), d.keys())
. Another way to create the same list ispairs = [(v, k) for (k, v) in d.items()]
.Iterating views while adding or deleting entries in the dictionary may raise a
RuntimeError
or fail to iterate over all entries.Changed in version 3.7: Dictionary order is guaranteed to be insertion order.
- x in dictview
Return
True
if x is in the underlying dictionary’s keys, values or items (in the latter case, x should be a(key, value)
tuple).
- reversed(dictview)
Return a reverse iterator over the keys, values or items of the dictionary. The view will be iterated in reverse order of the insertion.
Changed in version 3.8: Dictionary views are now reversible.
- dictview.mapping
Return a
types.MappingProxyType
that wraps the original dictionary to which the view refers.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': 2, 'sausage': 1, 'bacon': 1, 'spam': 500}
>>> keys = dishes.keys()
>>> values = dishes.values()
>>> # iteration
>>> n = 0
>>> for val in values:
... n += val
...
>>> print(n)
504
>>> # keys and values are iterated over in the same order (insertion order)
>>> list(keys)
['eggs', 'sausage', 'bacon', 'spam']
>>> list(values)
[2, 1, 1, 500]
>>> # view objects are dynamic and reflect dict changes
>>> del dishes['eggs']
>>> del dishes['sausage']
>>> list(keys)
['bacon', 'spam']
>>> # set operations
>>> keys & {'eggs', 'bacon', 'salad'}
{'bacon'}
>>> keys ^ {'sausage', 'juice'} == {'juice', 'sausage', 'bacon', 'spam'}
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 ofwith
statements using this context manager.An example of a context manager that returns itself is a file object. File objects return themselves from __enter__() to allow
open()
to be used as the context expression in awith
statement.An example of a context manager that returns a related object is the one returned by
decimal.localcontext()
. These managers set the active decimal context to a copy of the original decimal context and then return the copy. This allows changes to be made to the current decimal context in the body of thewith
statement without affecting code outside thewith
statement.
- contextmanager.__exit__(exc_type, exc_val, exc_tb)¶
Exit the runtime context and return a Boolean flag indicating if any exception that occurred should be suppressed. If an exception occurred while executing the body of the
with
statement, the arguments contain the exception type, value and traceback information. Otherwise, all three arguments areNone
.Returning a true value from this method will cause the
with
statement to suppress the exception and continue execution with the statement immediately following thewith
statement. Otherwise the exception continues propagating after this method has finished executing. Exceptions that occur during execution of this method will replace any exception that occurred in the body of thewith
statement.The exception passed in should never be reraised explicitly - instead, this method should return a false value to indicate that the method completed successfully and does not want to suppress the raised exception. This allows context management code to easily detect whether or not an
__exit__()
method has actually failed.
Python defines several context managers to support easy thread synchronisation,
prompt closure of files or other objects, and simpler manipulation of the active
decimal arithmetic context. The specific types are not treated specially beyond
their implementation of the context management protocol. See the
contextlib
module for some examples.
Python’s generators and the contextlib.contextmanager
decorator
provide a convenient way to implement these protocols. If a generator function is
decorated with the contextlib.contextmanager
decorator, it will return a
context manager implementing the necessary __enter__()
and
__exit__()
methods, rather than the iterator produced by an
undecorated generator function.
Note that there is no specific slot for any of these methods in the type structure for Python objects in the Python/C API. Extension types wanting to define these methods must provide them as a normal Python accessible method. Compared to the overhead of setting up the runtime context, the overhead of a single class dictionary lookup is negligible.
Type Annotation Types — Generic Alias, Union¶
The core built-in types for type annotations are Generic Alias and Union.
Generic Alias Type¶
GenericAlias
objects are generally created by
subscripting a class. They are most often used with
container classes, such as list
or
dict
. For example, list[int]
is a GenericAlias
object created
by subscripting the list
class with the argument int
.
GenericAlias
objects are intended primarily for use with
type annotations.
Note
It is generally only possible to subscript a class if the class implements
the special method __class_getitem__()
.
A GenericAlias
object acts as a proxy for a generic type,
implementing parameterized generics.
For a container class, the
argument(s) supplied to a subscription of the class may
indicate the type(s) of the elements an object contains. For example,
set[bytes]
can be used in type annotations to signify a set
in
which all the elements are of type bytes
.
For a class which defines __class_getitem__()
but is not a
container, the argument(s) supplied to a subscription of the class will often
indicate the return type(s) of one or more methods defined on an object. For
example, regular expressions
can be used on both the str
data
type and the bytes
data type:
If
x = re.search('foo', 'foo')
,x
will be a re.Match object where the return values ofx.group(0)
andx[0]
will both be of typestr
. We can represent this kind of object in type annotations with theGenericAlias
re.Match[str]
.If
y = re.search(b'bar', b'bar')
, (note theb
forbytes
),y
will also be an instance ofre.Match
, but the return values ofy.group(0)
andy[0]
will both be of typebytes
. In type annotations, we would represent this variety of re.Match objects withre.Match[bytes]
.
GenericAlias
objects are instances of the class
types.GenericAlias
, which can also be used to create GenericAlias
objects directly.
- T[X, Y, ...]
Creates a
GenericAlias
representing a typeT
parameterized by types X, Y, and more depending on theT
used. For example, a function expecting alist
containingfloat
elements:def average(values: list[float]) -> float: return sum(values) / len(values)
Another example for mapping objects, using a
dict
, which is a generic type expecting two type parameters representing the key type and the value type. In this example, the function expects adict
with keys of typestr
and values of typeint
:def send_post_request(url: str, body: dict[str, int]) -> None: ...
The builtin functions isinstance()
and issubclass()
do not accept
GenericAlias
types for their second argument:
>>> isinstance([1, 2], list[str])
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: isinstance() argument 2 cannot be a parameterized generic
The Python runtime does not enforce type annotations.
This extends to generic types and their type parameters. When creating
a container object from a GenericAlias
, the elements in the container are not checked
against their type. For example, the following code is discouraged, but will
run without errors:
>>> t = list[str]
>>> t([1, 2, 3])
[1, 2, 3]
Furthermore, parameterized generics erase type parameters during object creation:
>>> t = list[str]
>>> type(t)
<class 'types.GenericAlias'>
>>> l = t()
>>> type(l)
<class 'list'>
Calling repr()
or str()
on a generic shows the parameterized type:
>>> repr(list[int])
'list[int]'
>>> str(list[int])
'list[int]'
The __getitem__()
method of generic containers will raise an
exception to disallow mistakes like dict[str][str]
:
>>> dict[str][str]
Traceback (most recent call last):
...
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
>>> Y = TypeVar('Y')
>>> dict[str, Y][int]
dict[str, int]
Standard Generic Classes¶
The following standard library classes support parameterized generics. This list is non-exhaustive.
Special Attributes of GenericAlias
objects¶
All parameterized generics implement special read-only attributes.
- genericalias.__origin__¶
This attribute points at the non-parameterized generic class:
>>> list[int].__origin__ <class 'list'>
- genericalias.__args__¶
This attribute is a
tuple
(possibly of length 1) of generic types passed to the original__class_getitem__()
of the generic class:>>> dict[str, list[int]].__args__ (<class 'str'>, list[int])
- genericalias.__parameters__¶
This attribute is a lazily computed tuple (possibly empty) of unique type variables found in
__args__
:>>> from typing import TypeVar >>> T = TypeVar('T') >>> list[T].__parameters__ (~T,)
Note
A
GenericAlias
object withtyping.ParamSpec
parameters may not have correct__parameters__
after substitution becausetyping.ParamSpec
is intended primarily for static type checking.
- genericalias.__unpacked__¶
A boolean that is true if the alias has been unpacked using the
*
operator (seeTypeVarTuple
).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 typing.Union
.
- X | Y | ...
Defines a union object which holds types X, Y, and so forth.
X | Y
means either X or Y. It is equivalent totyping.Union[X, Y]
. For example, the following function expects an argument of typeint
orfloat
:def square(number: int | float) -> int | float: return number ** 2
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 is compatible with
typing.Union
:int | str == typing.Union[int, str]
Optional types can be spelled as a union with
None
:str | None == typing.Optional[str]
- isinstance(obj, union_object)
- issubclass(obj, union_object)
Calls to
isinstance()
andissubclass()
are also supported with a union object:>>> isinstance("", int | str) True
However, parameterized generics in union objects cannot be checked:
>>> isinstance(1, int | list[int]) # short-circuit evaluation True >>> isinstance([1], 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
types.UnionType
and used for isinstance()
checks. An object cannot be
instantiated from the type:
>>> import types
>>> isinstance(int | str, types.UnionType)
True
>>> types.UnionType()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: cannot create 'types.UnionType' instances
Note
The __or__()
method for type objects was added to support the syntax
X | Y
. If a metaclass implements __or__()
, the Union may
override it:
>>> class M(type):
... def __or__(self, other):
... return "Hello"
...
>>> class C(metaclass=M):
... pass
...
>>> C | int
'Hello'
>>> int | C
int | C
See also
PEP 604 – PEP proposing the X | Y
syntax and the Union type.
Added in version 3.10.
Other Built-in Types¶
The interpreter supports several other kinds of objects. Most of these support only one or two operations.
Modules¶
The only special operation on a module is attribute access: m.name
, where
m is a module and name accesses a name defined in m’s symbol table.
Module attributes can be assigned to. (Note that the import
statement is not, strictly speaking, an operation on a module object; import
foo
does not require a module object named foo to exist, rather it requires
an (external) definition for a module named foo somewhere.)
A special attribute of every module is __dict__
. This is the
dictionary containing the module’s symbol table. Modifying this dictionary will
actually change the module’s symbol table, but direct assignment to the
__dict__
attribute is not possible (you can write
m.__dict__['a'] = 1
, which defines m.a
to be 1
, but you can’t write
m.__dict__ = {}
). Modifying __dict__
directly is
not recommended.
Modules built into the interpreter are written like this: <module 'sys'
(built-in)>
. If loaded from a file, they are written as <module 'os' from
'/usr/local/lib/pythonX.Y/os.pyc'>
.
Classes and Class Instances¶
See Objects, values and types and Class definitions for these.
Functions¶
Function objects are created by function definitions. The only operation on a
function object is to call it: func(argument-list)
.
There are really two flavors of function objects: built-in functions and user-defined functions. Both support the same operation (to call the function), but the implementation is different, hence the different object types.
See Function definitions for more information.
Methods¶
Methods are functions that are called using the attribute notation. There are
two flavors: built-in methods (such as append()
on lists) and class instance 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 C:
... def method(self):
... pass
...
>>> c = C()
>>> c.method.whoami = 'my name is method' # can't set on the method
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'method' object has no attribute 'whoami'
>>> c.method.__func__.whoami = 'my name is method'
>>> c.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: <class '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 by slicing (see Slicings). 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 ...
.
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
>>> i = int('2' * 4300)
>>> len(str(i))
4300
>>> i_squared = i*i
>>> 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) == i*i # 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)
, orb"%d" % integer
.
The limitations do not apply to functions with a linear algorithm:
int(string, base)
with base 2, 4, 8, 16, or 32.Format Specification Mini-Language for hex, octal, and binary numbers.
str
todecimal.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 orPYTHONINTMAXSTRDIGITS=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 ofPYTHONINTMAXSTRDIGITS
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 ofsys.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()
andsys.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 == 0 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 0
.
Footnotes