内置类型

以下部分描述了解释器中内置的标准类型。

主要内置类型有数字、序列、映射、类、实例和异常。

有些多项集类是可变的。 它们用于添加、移除或重排其成员的方法将原地执行,并不返回特定的项,绝对不会返回多项集实例自身而是返回 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.

逻辑值检测

任何对象都可以进行逻辑值的检测,以便在 ifwhile 作为条件或是作为下文所述布尔运算的操作数来使用。

一个对象在默认情况下均被视为真值,除非当该对象被调用时其所属类定义了 __bool__() 方法且返回 False 或是定义了 __len__() 方法且返回零。 [1] 下面基本完整地列出了会被视为假值的内置对象:

  • 被定义为假值的常量: NoneFalse
  • 任何数值类型的零: 0, 0.0, 0j, Decimal(0), Fraction(0, 1)
  • 空的序列和多项集: '', (), [], {}, set(), range(0)

产生布尔值结果的运算和内置函数总是返回 0False 作为假值,1True 作为真值,除非另行说明。 (重要例外:布尔运算 orand 总是返回其中一个操作数。)

布尔运算 --- and, or, not

这些属于布尔运算,按优先级升序排列:

运算 结果 注释
x or y if x is false, then y, else x (1)
x and y if x is false, then x, else y (2)
not x if x is false, then True, else False (3)

注释:

  1. 这是个短路运算符,因此只有在第一个参数为假值时才会对第二个参数求值。
  2. 这是个短路运算符,因此只有在第一个参数为真值时才会对第二个参数求值。
  3. not 的优先级比非布尔运算符低,因此 not a == b 会被解读为 not (a == b)a == not b 会引发语法错误。

比较

在 Python 中有八种比较运算符。 它们的优先级相同(比布尔运算的优先级高)。 比较运算可以任意串连;例如,x < y <= z 等价于 x < y and y <= z,前者的不同之处在于 y 只被求值一次(但在两种情况下当 x < y 结果为假值时 z 都不会被求值)。

此表格汇总了比较运算:

运算 含义
< 严格小于
<= 小于或等于
> 严格大于
>= 大于或等于
== 等于
!= 不等于
is 对象标识
is not 否定的对象标识

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.

具有不同标识的类的实例比较结果通常为不相等,除非类定义了 __eq__() 方法。

一个类实例不能与相同类或的其他实例或其他类型的对象进行排序,除非该类定义了足够多的方法,包括 __lt__(), __le__(), __gt__() 以及 __ge__() (而如果你想实现常规意义上的比较操作,通常只要有 __lt__()__eq__() 就可以了)。

isis not 运算符无法自定义;并且它们可以被应用于任意两个对象而不会引发异常。

还有两种具有相同语法优先级的运算 innot in,它们被 iterable 或实现了 __contains__() 方法的类型所支持。

数字类型 --- 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.)

数字是由数字字面值或内置函数与运算符的结果来创建的。 不带修饰的整数字面值(包括十六进制、八进制和二进制数)会生成整数。 包含小数点或幂运算符的数字字面值会生成浮点数。 在数字字面值末尾加上 'j''J' 会生成虚数(实部为零的复数),你可以将其与整数或浮点数相加来得到具有实部和虚部的复数。

Python 完全支持混合算术:当一个二元运算符用于不同数字类型的操作数时,具有“较窄” 类型的操作数会被扩展为另操作数的类型,整数比浮点数更窄,浮点数又比复数更窄。 混合类型数字之间的比较也使用相同的规则。 [2] 构造器 int(), float()complex() 可被用于生成特定类型的数字。

所有数字类型(复数除外)都支持下列运算,按优先级升序排序(所有数字运算的优先级都高于比较运算):

运算 结果 注释 完整文档
x + y xy 的合计    
x - y xy 的差异    
x * y xy 的乘积    
x / y xy 的商    
x // y xy 的商数 (1)  
x % y remainder of x / y (2)  
-x x 取反    
+x x 不变    
abs(x) x 的绝对值或大小   abs()
int(x) x 转换为整数 (3)(6) int()
float(x) x 转换为浮点数 (4)(6) float()
complex(re, im) 一个带有实部 re 和虚部 im 的复数。im 默认为0。 (6) complex()
c.conjugate() 复数 c 的共轭    
divmod(x, y) (x // y, x % y) (2) divmod()
pow(x, y) xy 次幂 (5) pow()
x ** y xy 次幂 (5)  

注释:

  1. 也称为整数除法。 结果值是一个整数,但结果的类型不一定是 int。 运算结果总是向负无穷的方向舍入: 1//20, (-1)//2-1, 1//(-2)-1(-1)//(-2)0

  2. 不可用于复数。 而应在适当条件下使用 abs() 转换为浮点数。

  3. 从浮点数转换为整数会被舍入或是像在 C 语言中一样被截断;请参阅 math.floor()math.ceil() 函数查看转换的完整定义。

  4. float 也接受字符串 "nan" 和附带可选前缀 "+" 或 "-" 的 "inf" 分别表示非数字 (NaN) 以及正或负无穷。

  5. Python 将 pow(0, 0)0 ** 0 定义为 1,这是编程语言的普遍做法。

  6. 接受的数字字面值包括数码 09 或任何等效的 Unicode 字符(具有 Nd 特征属性的代码点)。

    See http://www.unicode.org/Public/12.0.0/ucd/extracted/DerivedNumericType.txt for a complete list of code points with the Nd property.

所有 numbers.Real 类型 (intfloat) 还包括下列运算:

运算 结果
math.trunc(x) x 截断为 Integral
round(x[, n]) x 舍入到 n 位小数,半数值会舍入到偶数。 如果省略 n,则默认为 0。
math.floor(x) <= x 的最大 Integral
math.ceil(x) >= x 的最小 Integral

有关更多的数字运算请参阅 mathcmath 模块。

整数类型的按位运算

按位运算只对整数有意义。 计算按位运算的结果,就相当于使用无穷多个二进制符号位对二的补码执行操作。

二进制按位运算的优先级全都低于数字运算,但又高于比较运算;一元运算 ~ 具有与其他一元算术运算 (+ and -) 相同的优先级。

此表格是以优先级升序排序的按位运算列表:

运算 结果 注释
x | y xy 按位 (4)
x ^ y xy 按位 异或 (4)
x & y xy 按位 (4)
x << n x 左移 n (1)(2)
x >> n x 右移 n (1)(3)
~x x 逐位取反  

注释:

  1. 负的移位数是非法的,会导致引发 ValueError
  2. 左移 n 位等价于不带溢出检测地乘以 pow(2, n)
  3. 右移 n 位等价于不带溢出检测地除以 pow(2, n)
  4. 使用带有至少一个额外符号扩展位的有限个二进制补码表示(有效位宽度为 1 + max(x.bit_length(), y.bit_length()) 或以上)执行这些计算就足以获得相当于有无数个符号位时的同样结果。

整数类型的附加方法

int 类型实现了 numbers.Integral abstract base class。 此外,它还提供了其他几个方法:

int.bit_length()

返回以二进制表示一个整数所需要的位数,不包括符号位和前面的零:

>>> n = -37
>>> bin(n)
'-0b100101'
>>> n.bit_length()
6

更准确地说,如果``x`` 非零,则 x.bit_length() 是使得 2**(k-1) <= abs(x) < 2**k 的唯一正整数 k。 同样地,当 abs(x) 小到足以具有正确的舍入对数时,则 k = 1 + int(log(abs(x), 2))。 如果 x 为零,则 x.bit_length() 返回 0

等价于:

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

3.1 新版功能.

int.to_bytes(length, byteorder, *, signed=False)

返回表示一个整数的字节数组。

>>> (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'

整数会使用 length 个字节来表示。 如果整数不能用给定的字节数来表示则会引发 OverflowError

byteorder 参数确定用于表示整数的字节顺序。 如果 byteorder"big",则最高位字节放在字节数组的开头。 如果 byteorder"little",则最高位字节放在字节数组的末尾。 要请求主机系统上的原生字节顺序,请使用 sys.byteorder 作为字节顺序值。

signed 参数确定是否使用二的补码来表示整数。 如果 signedFalse 并且给出的是负整数,则会引发 OverflowErrorsigned 的默认值为 False

3.2 新版功能.

classmethod int.from_bytes(bytes, byteorder, *, signed=False)

返回由给定字节数组所表示的整数。

>>> 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

bytes 参数必须为一个 bytes-like object 或是生成字节的可迭代对象。

byteorder 参数确定用于表示整数的字节顺序。 如果 byteorder"big",则最高位字节放在字节数组的开头。 如果 byteorder"little",则最高位字节放在字节数组的末尾。 要请求主机系统上的原生字节顺序,请使用 sys.byteorder 作为字节顺序值。

signed 参数指明是否使用二的补码来表示整数。

3.2 新版功能.

int.as_integer_ratio()

Return a pair of integers whose ratio is exactly equal to the original integer and with a positive denominator. The integer ratio of integers (whole numbers) is always the integer as the numerator and 1 as the denominator.

3.8 新版功能.

浮点类型的附加方法

float 类型实现了 numbers.Real abstract base class。 float 还具有以下附加方法。

float.as_integer_ratio()

返回一对整数,其比率正好等于原浮点数并且分母为正数。 无穷大会引发 OverflowError 而 NaN 则会引发 ValueError

float.is_integer()

如果 float 实例可用有限位整数表示则返回 True,否则返回 False:

>>> (-2.0).is_integer()
True
>>> (3.2).is_integer()
False

两个方法均支持与十六进制数字符串之间的转换。 由于 Python 浮点数在内部存储为二进制数,因此浮点数与 十进制数 字符串之间的转换往往会导致微小的舍入错误。 而十六进制数字符串却允许精确地表示和描述浮点数。 这在进行调试和数值工作时非常有用。

float.hex()

以十六进制字符串的形式返回一个浮点数表示。 对于有限浮点数,这种表示法将总是包含前导的 0x 和尾随的 p 加指数。

classmethod float.fromhex(s)

返回以十六进制字符串 s 表示的浮点数的类方法。 字符串 s 可以带有前导和尾随的空格。

请注意 float.hex() 是实例方法,而 float.fromhex() 是类方法。

十六进制字符串采用的形式为:

[sign] ['0x'] integer ['.' fraction] ['p' exponent]

可选的 sign 可以是 +-integerfraction 是十六进制数码组成的字符串,exponent 是带有可选前导符的十进制整数。 大小写没有影响,在 integer 或 fraction 中必须至少有一个十六进制数码。 此语法类似于 C99 标准的 6.4.4.2 小节中所描述的语法,也是 Java 1.5 以上所使用的语法。 特别地,float.hex() 的输出可以用作 C 或 Java 代码中的十六进制浮点数字面值,而由 C 的 %a 格式字符或 Java 的 Double.toHexString 所生成的十六进制数字符串由为 float.fromhex() 所接受。

请注意 exponent 是十进制数而非十六进制数,它给出要与系数相乘的 2 的幂次。 例如,十六进制数字符串 0x3.a7p10 表示浮点数 (3 + 10./16 + 7./16**2) * 2.0**103740.0:

>>> float.fromhex('0x3.a7p10')
3740.0

3740.0 应用反向转换会得到另一个代表相同数值的十六进制数字符串:

>>> float.hex(3740.0)
'0x1.d380000000000p+11'

数字类型的哈希运算

对于可能为不同类型的数字 xy,要求 x == y 时必定 hash(x) == hash(y) (详情参见 __hash__() 方法的文档)。 为了便于在各种数字类型 (包括 int, float, decimal.Decimalfractions.Fraction) 上实现并保证效率,Python 对数字类型的哈希运算是基于为任意有理数定义统一的数学函数,因此该运算对 intfractions.Fraction 的全部实例,以及 floatdecimal.Decimal 的全部有限实例均可用。 从本质上说,此函数是通过以一个固定质数 P 进行 P 降模给出的。 P 的值在 Python 中可以 sys.hash_infomodulus 属性的形式被访问。

CPython implementation detail: 目前所用的质数设定,在 C long 为 32 位的机器上 P = 2**31 - 1 而在 C long 为 64 位的机器上 P = 2**61 - 1

详细规则如下所述:

  • 如果 x = m / n 是一个非负的有理数且 n 不可被 P 整除,则定义 hash(x)m * invmod(n, P) % P,其中 invmod(n, P) 是对 nP 取反。
  • 如果 x = m / n 是一个非负的有理数且 n 可被 P 整除(但 m 不能)则 n 不能对 P 降模,以上规则不适用;在此情况下则定义 hash(x) 为常数值 sys.hash_info.inf
  • 如果 x = m / n 是一个负的有理数则定义 hash(x)-hash(-x)。 如果结果哈希值为 -1 则将其替换为 -2
  • 特定值 sys.hash_info.inf, -sys.hash_info.infsys.hash_info.nan 被用作正无穷、负无穷和空值(所分别对应的)哈希值。 (所有可哈希的空值都具有相同的哈希值。)
  • 对于一个 complexz,会通过计算 hash(z.real) + sys.hash_info.imag * hash(z.imag) 将实部和虚部的哈希值结合起来,并进行降模 2**sys.hash_info.width 以使其处于 range(-2**(sys.hash_info.width - 1), 2**(sys.hash_info.width - 1)) 范围之内。 同样地,如果结果为 -1 则将其替换为 -2

为了阐明上述规则,这里有一些等价于内置哈希算法的 Python 代码示例,可用于计算有理数、floatcomplex 的哈希值:

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 sys.hash_info.nan
    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

迭代器类型

Python 支持在容器中进行迭代的概念。 这是通过使用两个单独方法来实现的;它们被用于允许用户自定义类对迭代的支持。 将在下文中详细描述的序列总是支持迭代方法。

容器对象要提供迭代支持,必须定义一个方法:

container.__iter__()

返回一个迭代器对象。 该对象需要支持下文所述的迭代器协议。 如果容器支持不同的迭代类型,则可以提供额外的方法来专门地请求不同迭代类型的迭代器。 (支持多种迭代形式的对象的例子有同时支持广度优先和深度优先遍历的树结构。) 此方法对应于 Python/C API 中 Python 对象类型结构体的 tp_iter 槽位。

迭代器对象自身需要支持以下两个方法,它们共同组成了 迭代器协议:

iterator.__iter__()

返回迭代器对象本身。 这是同时允许容器和迭代器配合 forin 语句使用所必须的。 此方法对应于 Python/C API 中 Python 对象类型结构体的 tp_iter 槽位。

iterator.__next__()

从容器中返回下一项。 如果已经没有项可返回,则会引发 StopIteration 异常。 此方法对应于 Python/C API 中 Python 对象类型结构体的 tp_iternext 槽位。

Python 定义了几种迭代器对象以支持对一般和特定序列类型、字典和其他更特别的形式进行迭代。 除了迭代器协议的实现,特定类型的其他性质对迭代操作来说都不重要。

一旦迭代器的 __next__() 方法引发了 StopIteration,它必须一直对后续调用引发同样的异常。 不遵循此行为特性的实现将无法正常使用。

生成器类型

Python 的 generator 提供了一种实现迭代器协议的便捷方式。 如果容器对象 __iter__() 方法被实现为一个生成器,它将自动返回一个迭代器对象(从技术上说是一个生成器对象),该对象提供 __iter__()__next__() 方法。 有关生成器的更多信息可以参阅 yield 表达式的文档

序列类型 --- list, tuple, range

有三种基本序列类型:list, tuple 和 range 对象。 为处理 二进制数据文本字符串 而特别定制的附加序列类型会在专门的小节中描述。

常用序列操作

大多数序列类型,包括可变类型和不可变类型都支持下表中的操作。 collections.abc.Sequence ABC 被提供用来更容易地在自定义序列类型上正确地实现这些操作。

此表按优先级升序列出了序列操作。 在表格中,st 是具有相同类型的序列,n, i, jk 是整数而 x 是任何满足 s 所规定的类型和值限制的任意对象。

innot in 操作具有与比较操作相同的优先级。 + (拼接) 和 * (重复) 操作具有与对应数值运算相同的优先级。 [3]

运算 结果 注释
x in s 如果 s 中的某项等于 x 则结果为 True,否则为 False (1)
x not in s 如果 s 中的某项等于 x 则结果为 False,否则为 True (1)
s + t st 相拼接 (6)(7)
s * nn * s 相当于 s 与自身进行 n 次拼接 (2)(7)
s[i] s 的第 i 项,起始为 0 (3)
s[i:j] sij 的切片 (3)(4)
s[i:j:k] sij 步长为 k 的切片 (3)(5)
len(s) s 的长度  
min(s) s 的最小项  
max(s) s 的最大项  
s.index(x[, i[, j]]) xs 中首次出现项的索引号(索引号在 i 或其后且在 j 之前) (8)
s.count(x) xs 中出现的总次数  

相同类型的序列也支持比较。 特别地,tuple 和 list 的比较是通过比较对应元素的字典顺序。 这意味着想要比较结果相等,则每个元素比较结果都必须相等,并且两个序列长度必须相同。 (完整细节请参阅语言参考的 比较运算 部分。)

注释:

  1. While the in and not in operations are used only for simple containment testing in the general case, some specialised sequences (such as str, bytes and bytearray) also use them for subsequence testing:

    >>> "gg" in "eggs"
    True
    
  2. Values of n less than 0 are treated as 0 (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 of lists 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?.

  3. If i or j is negative, the index is relative to the end of sequence s: len(s) + i or len(s) + j is substituted. But note that -0 is still 0.

  4. 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 than len(s), use len(s). If i is omitted or None, use 0. If j is omitted or None, use len(s). If i is greater than or equal to j, the slice is empty.

  5. 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 that 0 <= n < (j-i)/k. In other words, the indices are i, 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 to len(s) if they are greater. When k is negative, i and j are reduced to len(s) - 1 if they are greater. If i or j are omitted or None, they become "end" values (which end depends on the sign of k). Note, k cannot be zero. If k is None, it is treated like 1.

  6. Concatenating immutable sequences always results in a new object. This means that building up a sequence by repeated concatenation will have a quadratic runtime cost in the total sequence length. To get a linear runtime cost, you must switch to one of the alternatives below:

    • if concatenating str objects, you can build a list and use str.join() at the end or else write to an io.StringIO instance and retrieve its value when complete
    • if concatenating bytes objects, you can similarly use bytes.join() or io.BytesIO, or you can do in-place concatenation with a bytearray object. bytearray objects are mutable and have an efficient overallocation mechanism
    • if concatenating tuple objects, extend a list instead
    • for other types, investigate the relevant class documentation
  7. Some sequence types (such as range) only support item sequences that follow specific patterns, and hence don't support sequence concatenation or repetition.

  8. index raises ValueError 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 using s[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).

运算 结果 注释
s[i] = x item i of s is replaced by x  
s[i:j] = t slice of s from i to j is replaced by the contents of the iterable t  
del s[i:j] same as s[i:j] = []  
s[i:j:k] = t the elements of s[i:j:k] are replaced by those of t (1)
del s[i:j:k] removes the elements of s[i:j:k] from the list  
s.append(x) appends x to the end of the sequence (same as s[len(s):len(s)] = [x])  
s.clear() removes all items from s (same as del s[:]) (5)
s.copy() creates a shallow copy of s (same as s[:]) (5)
s.extend(t) or s += t extends s with the contents of t (for the most part the same as s[len(s):len(s)] = t)  
s *= n updates s with its contents repeated n times (6)
s.insert(i, x) inserts x into s at the index given by i (same as s[i:i] = [x])  
s.pop([i]) retrieves the item at i and also removes it from s (2)
s.remove(x) 删除 s 中第一个 s[i] 等于 x 的项目。 (3)
s.reverse() 就地将列表中的元素逆序。 (4)

注释:

  1. t must have the same length as the slice it is replacing.

  2. The optional argument i defaults to -1, so that by default the last item is removed and returned.

  3. remove raises ValueError when x is not found in s.

  4. 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.

  5. clear() and copy() are included for consistency with the interfaces of mutable containers that don't support slicing operations (such as dict and set)

    3.3 新版功能: clear()copy() 方法。

  6. 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 for s * n under 常用序列操作.

列表

列表是可变序列,通常用于存放同类项目的集合(其中精确的相似程度将根据应用而变化)。

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() or list(iterable)

The constructor builds a list whose items are the same and in the same order as iterable's items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a list, a copy is made and returned, similar to iterable[:]. For example, list('abc') returns ['a', 'b', 'c'] and list( (1, 2, 3) ) returns [1, 2, 3]. If no argument is given, the constructor creates a new empty list, [].

Many other operations also produce lists, including the sorted() built-in.

Lists implement all of the common and mutable sequence operations. Lists also provide the following additional method:

sort(*, key=None, reverse=False)

This method sorts the list in place, using only < comparisons between items. Exceptions are not suppressed - if any comparison operations fail, the entire sort operation will fail (and the list will likely be left in a partially modified state).

sort() accepts two arguments that can only be passed by keyword (keyword-only arguments):

key specifies a function of one argument that is used to extract a comparison key from each list element (for example, key=str.lower). The key corresponding to each item in the list is calculated once and then used for the entire sorting process. The default value of None means that list items are sorted directly without calculating a separate key value.

The functools.cmp_to_key() utility is available to convert a 2.x style cmp function to a key function.

reverse 为一个布尔值。 如果设为 True,则每个列表元素将按反向顺序比较进行排序。

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 排序指南.

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.

元组

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() or tuple(iterable)

The constructor builds a tuple whose items are the same and in the same order as iterable's items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a tuple, it is returned unchanged. For example, tuple('abc') returns ('a', 'b', 'c') and tuple( [1, 2, 3] ) returns (1, 2, 3). If no argument is given, the constructor creates a new empty tuple, ().

Note that it is actually the comma which makes a tuple, not the parentheses. The parentheses are optional, except in the empty tuple case, or when they are needed to avoid syntactic ambiguity. For example, f(a, b, c) is a function call with three arguments, while f((a, b, c)) is a function call with a 3-tuple as the sole argument.

Tuples implement all of the common sequence operations.

For heterogeneous collections of data where access by name is clearer than access by index, collections.namedtuple() may be a more appropriate choice than a simple tuple object.

Ranges

The range type represents an immutable sequence of numbers and is commonly used for looping a specific number of times in for loops.

class range(stop)
class range(start, stop[, step])

The arguments to the range constructor must be integers (either built-in int or any object that implements the __index__ special method). If the step argument is omitted, it defaults to 1. If the start argument is omitted, it defaults to 0. If step is zero, ValueError is raised.

For a positive step, the contents of a range r are determined by the formula r[i] = start + step*i where i >= 0 and r[i] < stop.

For a negative step, the contents of the range are still determined by the formula r[i] = start + step*i, but the constraints are i >= 0 and r[i] > stop.

A range object will be empty if r[0] does not meet the value constraint. Ranges do support negative indices, but these are interpreted as indexing from the end of the sequence determined by the positive indices.

Ranges containing absolute values larger than sys.maxsize are permitted but some features (such as len()) may raise OverflowError.

Range examples:

>>> list(range(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> list(range(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 序列类型 --- 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).)

在 3.2 版更改: Implement the Sequence ABC. Support slicing and negative indices. Test int objects for membership in constant time instead of iterating through all items.

在 3.3 版更改: Define '==' and '!=' to compare range objects based on the sequence of values they define (instead of comparing based on object identity).

3.3 新版功能: The start, stop and step attributes.

参见

  • 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 字符串和字节串字面值 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.

在 3.3 版更改: 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) returns object.__str__(), which is the "informal" or nicely printable string representation of object. For string objects, this is the string itself. If object does not have a __str__() method, then str() falls back to returning repr(object).

If at least one of encoding or errors is given, object should be a bytes-like object (e.g. bytes or bytearray). In this case, if object is a bytes (or bytearray) object, then str(bytes, encoding, errors) is equivalent to bytes.decode(encoding, errors). Otherwise, the bytes object underlying the buffer object is obtained before calling bytes.decode(). See Binary Sequence Types --- bytes, bytearray, memoryview and 缓冲协议 for information on buffer objects.

Passing a bytes object to str() without the encoding or errors arguments falls under the first case of returning the informal string representation (see also the -b command-line option to Python). For example:

>>> str(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 格式化字符串字面值 and Format String Syntax sections. In addition, see the 文本处理服务 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 文本处理服务 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.

str.casefold()

Return a casefolded copy of the string. Casefolded strings may be used for caseless matching.

Casefolding is similar to lowercasing but more aggressive because it is intended to remove all case distinctions in a string. For example, the German lowercase letter 'ß' is equivalent to "ss". Since it is already lowercase, lower() would do nothing to 'ß'; casefold() converts it to "ss".

The casefolding algorithm is described in section 3.13 of the Unicode Standard.

3.3 新版功能.

str.center(width[, fillchar])

Return centered in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to len(s).

str.count(sub[, start[, end]])

Return the number of non-overlapping occurrences of substring sub in the range [start, end]. Optional arguments start and end are interpreted as in slice notation.

str.encode(encoding="utf-8", errors="strict")

Return an encoded version of the string as a bytes object. Default encoding is 'utf-8'. errors may be given to set a different error handling scheme. The default for errors is 'strict', meaning that encoding errors raise a UnicodeError. Other possible values are 'ignore', 'replace', 'xmlcharrefreplace', 'backslashreplace' and any other name registered via codecs.register_error(), see section Error Handlers. For a list of possible encodings, see section Standard Encodings.

在 3.1 版更改: Support for keyword arguments added.

str.endswith(suffix[, start[, end]])

Return True if the string ends with the specified suffix, otherwise return False. suffix can also be a tuple of suffixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.

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.

注解

The find() method should be used only if you need to know the position of sub. To check if sub is a substring or not, use the in operator:

>>> 'Py' in 'Python'
True
str.format(*args, **kwargs)

Perform a string formatting operation. The string on which this method is called can contain literal text or replacement fields delimited by braces {}. Each replacement field contains either the numeric index of a positional argument, or the name of a keyword argument. Returns a copy of the string where each replacement field is replaced with the string value of the corresponding argument.

>>> "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.

注解

When formatting a number (int, float, complex, decimal.Decimal and subclasses) with the n type (ex: '{:n}'.format(1234)), the function temporarily sets the LC_CTYPE locale to the LC_NUMERIC locale to decode decimal_point and thousands_sep fields of localeconv() if they are non-ASCII or longer than 1 byte, and the LC_NUMERIC locale is different than the LC_CTYPE locale. This temporary change affects other threads.

在 3.7 版更改: When formatting a number with the n type, the function sets temporarily the LC_CTYPE locale to the LC_NUMERIC locale in some cases.

str.format_map(mapping)

Similar to str.format(**mapping), except that mapping is used directly and not copied to a dict. This is useful if for example mapping is a dict subclass:

>>> class Default(dict):
...     def __missing__(self, key):
...         return key
...
>>> '{name} was born in {country}'.format_map(Default(name='Guido'))
'Guido was born in country'

3.2 新版功能.

str.index(sub[, start[, end]])

Like find(), but raise ValueError 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 character c is alphanumeric if one of the following returns True: c.isalpha(), c.isdecimal(), c.isdigit(), or c.isnumeric().

str.isalpha()

Return true if all characters in the string are alphabetic and there is at least one character, false otherwise. Alphabetic characters are those characters defined in the Unicode character database as "Letter", i.e., those with general category property being one of "Lm", "Lt", "Lu", "Ll", or "Lo". Note that this is different from the "Alphabetic" property defined in the Unicode Standard.

str.isascii()

Return true if the string is empty or all characters in the string are ASCII, false otherwise. ASCII characters have code points in the range U+0000-U+007F.

3.7 新版功能.

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 标识符和关键字.

Call keyword.iskeyword() to test whether string s is a reserved identifier, such as def and class.

Example:

>>> from keyword import iskeyword

>>> 'hello'.isidentifier(), iskeyword('hello')
True, False
>>> 'def'.isidentifier(), iskeyword('def')
True, True
str.islower()

Return true if all cased characters [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 when repr() is invoked on a string. It has no bearing on the handling of strings written to sys.stdout or sys.stderr.)

str.isspace()

Return true if there are only whitespace characters in the string and there is at least one character, false otherwise. Whitespace characters are those characters defined in the Unicode character database as "Other" or "Separator" and those with bidirectional property being one of "WS", "B", or "S".

str.istitle()

Return true if the string is a titlecased string and there is at least one character, for example uppercase characters may only follow uncased characters and lowercase characters only cased ones. Return false otherwise.

str.isupper()

Return true if all cased characters [4] in the string are uppercase and there is at least one cased character, false otherwise.

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, including bytes objects. The separator between elements is the string providing this method.

str.ljust(width[, fillchar])

Return the string left justified in a string of length width. Padding is done using the specified fillchar (default is an ASCII space). The original string is returned if width is less than or equal to len(s).

str.lower()

Return a copy of the string with all the cased characters [4] converted to lowercase.

The lowercasing algorithm used is described in section 3.13 of the Unicode Standard.

str.lstrip([chars])

Return a copy of the string with leading characters removed. The chars argument is a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped:

>>> '   spacious   '.lstrip()
'spacious   '
>>> 'www.example.com'.lstrip('cmowz.')
'example.com'
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.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 raises ValueError 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 like split() 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'
str.split(sep=None, maxsplit=-1)

Return a list of the words in the string, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done (thus, the list will have at most maxsplit+1 elements). If maxsplit is not specified or -1, then there is no limit on the number of splits (all possible splits are made).

If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty strings (for example, '1,,2'.split(',') returns ['1', '', '2']). The sep argument may consist of multiple characters (for example, '1<>2<>3'.split('<>') returns ['1', '2', '3']). Splitting an empty string with a specified separator returns [''].

例如:

>>> '1,2,3'.split(',')
['1', '2', '3']
>>> '1,2,3'.split(',', maxsplit=1)
['1', '2,3']
>>> '1,2,,3,'.split(',')
['1', '2', '', '3', '']

If sep is not specified or is None, a different splitting algorithm is applied: runs of consecutive whitespace are regarded as a single separator, and the result will contain no empty strings at the start or end if the string has leading or trailing whitespace. Consequently, splitting an empty string or a string consisting of just whitespace with a None separator returns [].

例如:

>>> '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])

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 描述
\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

在 3.2 版更改: \v and \f added to list of line boundaries.

例如:

>>> '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 return False. prefix can also be a tuple of prefixes to look for. With optional start, test string beginning at that position. With optional end, stop comparing string at that position.

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.

例如:

>>> '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"

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)[0].upper() +
...                              mo.group(0)[1:].lower(),
...                   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; return None, to delete the character from the return string; or raise a LookupError exception, to map the character to itself.

You can use str.maketrans() to create a translation map from character-to-character mappings in different formats.

See also the codecs module for a more flexible approach to custom character mappings.

str.upper()

Return a copy of the string with all the cased characters [4] converted to uppercase. Note that s.upper().isupper() might be False if s contains uncased characters or if the Unicode category of the resulting character(s) is not "Lu" (Letter, uppercase), but e.g. "Lt" (Letter, titlecase).

The uppercasing algorithm used is described in section 3.13 of the Unicode Standard.

str.zfill(width)

Return a copy of the string left filled with ASCII '0' digits to make a string of length width. A leading sign prefix ('+'/'-') is handled by inserting the padding after the sign character rather than before. The original string is returned if width is less than or equal to len(s).

例如:

>>> "42".zfill(5)
'00042'
>>> "-42".zfill(5)
'-0042'

printf-style String Formatting

注解

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:

  1. The '%' character, which marks the start of the specifier.
  2. Mapping key (optional), consisting of a parenthesised sequence of characters (for example, (somename)).
  3. Conversion flags (optional), which affect the result of some conversion types.
  4. 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.
  5. 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.
  6. Length modifier (optional).
  7. 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:

标志 含义
'#' The value conversion will use the "alternate form" (where defined below).
'0' The conversion will be zero padded for numeric values.
'-' The converted value is left adjusted (overrides the '0' conversion if both are given).
' ' (a space) A blank should be left before a positive number (or empty string) produced by a signed conversion.
'+' A sign character ('+' or '-') will precede the conversion (overrides a "space" flag).

A length modifier (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 含义 注释
'd' Signed integer decimal.  
'i' Signed integer decimal.  
'o' Signed octal value. (1)
'u' Obsolete type -- it is identical to 'd'. (6)
'x' Signed hexadecimal (lowercase). (2)
'X' Signed hexadecimal (uppercase). (2)
'e' Floating point exponential format (lowercase). (3)
'E' Floating point exponential format (uppercase). (3)
'f' Floating point decimal format. (3)
'F' Floating point decimal format. (3)
'g' Floating point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. (4)
'G' Floating point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. (4)
'c' Single character (accepts integer or single character string).  
'r' String (converts any Python object using repr()). (5)
's' String (converts any Python object using str()). (5)
'a' String (converts any Python object using ascii()). (5)
'%' No argument is converted, results in a '%' character in the result.  

注释:

  1. The alternate form causes a leading octal specifier ('0o') to be inserted before the first digit.

  2. 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.

  3. 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.

  4. 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.

  5. If precision is N, the output is truncated to N characters.

  6. See PEP 237.

Since Python strings have an explicit length, %s conversions do not assume that '\0' is the end of the string.

在 3.1 版更改: %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.

字节对象

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 字符串和字节串字面值 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 trigger ValueError). This is done deliberately to emphasise that while many binary formats include ASCII based elements and can be usefully manipulated with some text-oriented algorithms, this is not generally the case for arbitrary binary data (blindly applying text processing algorithms to binary data formats that are not ASCII compatible will usually lead to data corruption).

In addition to the literal forms, bytes objects can be created in a number of other ways:

  • A zero-filled bytes object of a specified length: bytes(10)
  • From an iterable of integers: bytes(range(20))
  • Copying existing binary data via the buffer protocol: bytes(obj)

Also see the bytes built-in.

Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data. Accordingly, the bytes type has an additional class method to read data in that format:

classmethod fromhex(string)

This bytes class method returns a bytes object, decoding the given string object. The string must contain two hexadecimal digits per byte, with ASCII whitespace being ignored.

>>> bytes.fromhex('2Ef0 F1f2  ')
b'.\xf0\xf1\xf2'

在 3.7 版更改: 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()

Return a string object containing two hexadecimal digits for each byte in the instance.

>>> b'\xf0\xf1\xf2'.hex()
'f0f1f2'

3.5 新版功能.

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).

注解

For Python 2.x users: In the Python 2.x series, a variety of implicit conversions between 8-bit strings (the closest thing 2.x offers to a built-in binary data type) and Unicode strings were permitted. This was a backwards compatibility workaround to account for the fact that Python originally only supported 8-bit text, and Unicode text was a later addition. In Python 3.x, those implicit conversions are gone - conversions between 8-bit binary data and Unicode text must be explicit, and bytes and string objects will always compare unequal.

Bytearray Objects

bytearray objects are a mutable counterpart to bytes objects.

class bytearray([source[, encoding[, errors]]])

There is no dedicated literal syntax for bytearray objects, instead they are always created by calling the constructor:

  • Creating an empty instance: bytearray()
  • Creating a zero-filled instance with a given length: bytearray(10)
  • From an iterable of integers: bytearray(range(20))
  • Copying existing binary data via the buffer protocol: bytearray(b'Hi!')

As bytearray objects are mutable, they support the mutable sequence operations in addition to the common bytes and bytearray operations described in Bytes and Bytearray Operations.

Also see the bytearray built-in.

Since 2 hexadecimal digits correspond precisely to a single byte, hexadecimal numbers are a commonly used format for describing binary data. Accordingly, the bytearray type has an additional class method to read data in that format:

classmethod fromhex(string)

This bytearray class method returns bytearray object, decoding the given string object. The string must contain two hexadecimal digits per byte, with ASCII whitespace being ignored.

>>> bytearray.fromhex('2Ef0 F1f2  ')
bytearray(b'.\xf0\xf1\xf2')

在 3.7 版更改: 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()

Return a string object containing two hexadecimal digits for each byte in the instance.

>>> bytearray(b'\xf0\xf1\xf2').hex()
'f0f1f2'

3.5 新版功能.

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.

注解

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.

注解

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.

在 3.3 版更改: Also accept an integer in the range 0 to 255 as the subsequence.

bytes.decode(encoding="utf-8", errors="strict")
bytearray.decode(encoding="utf-8", errors="strict")

Return a string decoded from the given bytes. Default encoding is 'utf-8'. errors may be given to set a different error handling scheme. The default for errors is 'strict', meaning that encoding errors raise a UnicodeError. Other possible values are 'ignore', 'replace' and any other name registered via codecs.register_error(), see section Error Handlers. For a list of possible encodings, see section Standard Encodings.

注解

Passing the encoding argument to str allows decoding any bytes-like object directly, without needing to make a temporary bytes or bytearray object.

在 3.1 版更改: Added support for keyword arguments.

bytes.endswith(suffix[, start[, end]])
bytearray.endswith(suffix[, start[, end]])

Return True if the binary data ends with the specified suffix, otherwise return False. suffix can also be a tuple of suffixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.

The suffix(es) to search for may be any bytes-like object.

bytes.find(sub[, start[, end]])
bytearray.find(sub[, start[, end]])

Return the lowest index in the data where the subsequence sub is found, such that sub is contained in the slice s[start:end]. Optional arguments start and end are interpreted as in slice notation. Return -1 if sub is not found.

The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.

注解

The find() method should be used only if you need to know the position of sub. To check if sub is a substring or not, use the in operator:

>>> b'Py' in b'Python'
True

在 3.3 版更改: Also accept an integer in the range 0 to 255 as the subsequence.

bytes.index(sub[, start[, end]])
bytearray.index(sub[, start[, end]])

Like find(), but raise ValueError when the subsequence is not found.

The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.

在 3.3 版更改: Also accept an integer in the range 0 to 255 as the subsequence.

bytes.join(iterable)
bytearray.join(iterable)

Return a bytes or bytearray object which is the concatenation of the binary data sequences in iterable. A TypeError will be raised if there are any values in iterable that are not bytes-like objects, including str objects. The separator between elements is the contents of the bytes or bytearray object providing this method.

static bytes.maketrans(from, to)
static bytearray.maketrans(from, to)

This static method returns a translation table usable for bytes.translate() that will map each character in from into the character at the same position in to; from and to must both be bytes-like objects and have the same length.

3.1 新版功能.

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.

注解

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.

在 3.3 版更改: Also accept an integer in the range 0 to 255 as the subsequence.

bytes.rindex(sub[, start[, end]])
bytearray.rindex(sub[, start[, end]])

Like rfind() but raises ValueError when the subsequence sub is not found.

The subsequence to search for may be any bytes-like object or an integer in the range 0 to 255.

在 3.3 版更改: 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 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.startswith(prefix[, start[, end]])
bytearray.startswith(prefix[, start[, end]])

Return True if the binary data starts with the specified prefix, otherwise return False. prefix can also be a tuple of prefixes to look for. With optional start, test beginning at that position. With optional end, stop comparing at that position.

The prefix(es) to search for may be any bytes-like object.

bytes.translate(table, delete=b'')
bytearray.translate(table, delete=b'')

Return a copy of the bytes or bytearray object where all bytes occurring in the optional argument delete are removed, and the remaining bytes have been mapped through the given translation table, which must be a bytes object of length 256.

You can use the bytes.maketrans() method to create a translation table.

Set the table argument to None for translations that only delete characters:

>>> b'read this short text'.translate(None, b'aeiou')
b'rd ths shrt txt'

在 3.6 版更改: 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 to len(s).

注解

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 to len(s).

注解

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.

注解

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 to len(s).

注解

The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.

bytes.rsplit(sep=None, maxsplit=-1)
bytearray.rsplit(sep=None, maxsplit=-1)

Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given, at most maxsplit splits are done, the rightmost ones. If sep is not specified or None, any subsequence consisting solely of ASCII whitespace is a separator. Except for splitting from the right, rsplit() behaves like split() which is described in detail below.

bytes.rstrip([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.

注解

The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.

bytes.split(sep=None, maxsplit=-1)
bytearray.split(sep=None, maxsplit=-1)

Split the binary sequence into subsequences of the same type, using sep as the delimiter string. If maxsplit is given and non-negative, at most maxsplit splits are done (thus, the list will have at most maxsplit+1 elements). If maxsplit is not specified or is -1, then there is no limit on the number of splits (all possible splits are made).

If sep is given, consecutive delimiters are not grouped together and are deemed to delimit empty subsequences (for example, b'1,,2'.split(b',') returns [b'1', b'', b'2']). The sep argument may consist of a multibyte sequence (for example, b'1<>2<>3'.split(b'<>') returns [b'1', b'2', b'3']). Splitting an empty sequence with a specified separator returns [b''] or [bytearray(b'')] depending on the type of object being split. The sep argument may be any bytes-like object.

例如:

>>> b'1,2,3'.split(b',')
[b'1', b'2', b'3']
>>> b'1,2,3'.split(b',', maxsplit=1)
[b'1', b'2,3']
>>> b'1,2,,3,'.split(b',')
[b'1', b'2', b'', b'3', b'']

If sep is not specified or is None, a different splitting algorithm is applied: runs of consecutive ASCII whitespace are regarded as a single separator, and the result will contain no empty strings at the start or end if the sequence has leading or trailing whitespace. Consequently, splitting an empty sequence or a sequence consisting solely of ASCII whitespace without a specified separator returns [].

例如:

>>> 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.

注解

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.

注解

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'

注解

The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.

bytes.isalnum()
bytearray.isalnum()

Return true if all bytes in the sequence are alphabetical ASCII characters or ASCII decimal digits and the sequence is not empty, false otherwise. Alphabetic ASCII characters are those byte values in the sequence b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'. ASCII decimal digits are those byte values in the sequence b'0123456789'.

例如:

>>> 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 sequence b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'.

例如:

>>> 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.

3.7 新版功能.

bytes.isdigit()
bytearray.isdigit()

Return true if all bytes in the sequence are ASCII decimal digits and the sequence is not empty, false otherwise. ASCII decimal digits are those byte values in the sequence b'0123456789'.

例如:

>>> 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.

例如:

>>> 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 sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

bytes.isspace()
bytearray.isspace()

Return true if all bytes in the sequence are ASCII whitespace and the sequence is not empty, false otherwise. ASCII whitespace characters are those byte values in the sequence b' \t\n\r\x0b\f' (space, tab, newline, carriage return, vertical tab, form feed).

bytes.istitle()
bytearray.istitle()

Return true if the sequence is ASCII titlecase and the sequence is not empty, false otherwise. See bytes.title() for more details on the definition of "titlecase".

例如:

>>> 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.

例如:

>>> 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 sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

bytes.lower()
bytearray.lower()

Return a copy of the sequence with all the uppercase ASCII characters converted to their corresponding lowercase counterpart.

例如:

>>> 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 sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

注解

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.

例如:

>>> 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.

例如:

>>> 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 sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

Unlike str.swapcase(), it is always the case that bin.swapcase().swapcase() == bin for the binary versions. Case conversions are symmetrical in ASCII, even though that is not generally true for arbitrary Unicode code points.

注解

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.

例如:

>>> 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 sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'. All other byte values are uncased.

The algorithm uses a simple language-independent definition of a word as groups of consecutive letters. The definition works in many contexts but it means that apostrophes in contractions and possessives form word boundaries, which may not be the desired result:

>>> 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."

注解

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.

例如:

>>> 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 sequence b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

注解

The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.

bytes.zfill(width)
bytearray.zfill(width)

Return a copy of the sequence left filled with ASCII b'0' digits to make a sequence of length width. A leading sign prefix (b'+'/ b'-') is handled by inserting the padding after the sign character rather than before. For bytes objects, the original sequence is returned if width is less than or equal to len(seq).

例如:

>>> b"42".zfill(5)
b'00042'
>>> b"-42".zfill(5)
b'-0042'

注解

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

注解

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:

  1. The '%' character, which marks the start of the specifier.
  2. Mapping key (optional), consisting of a parenthesised sequence of characters (for example, (somename)).
  3. Conversion flags (optional), which affect the result of some conversion types.
  4. 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.
  5. 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.
  6. Length modifier (optional).
  7. 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:

标志 含义
'#' The value conversion will use the "alternate form" (where defined below).
'0' The conversion will be zero padded for numeric values.
'-' The converted value is left adjusted (overrides the '0' conversion if both are given).
' ' (a space) A blank should be left before a positive number (or empty string) produced by a signed conversion.
'+' A sign character ('+' or '-') will precede the conversion (overrides a "space" flag).

A length modifier (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 含义 注释
'd' Signed integer decimal.  
'i' Signed integer decimal.  
'o' Signed octal value. (1)
'u' Obsolete type -- it is identical to 'd'. (8)
'x' Signed hexadecimal (lowercase). (2)
'X' Signed hexadecimal (uppercase). (2)
'e' Floating point exponential format (lowercase). (3)
'E' Floating point exponential format (uppercase). (3)
'f' Floating point decimal format. (3)
'F' Floating point decimal format. (3)
'g' Floating point format. Uses lowercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. (4)
'G' Floating point format. Uses uppercase exponential format if exponent is less than -4 or not less than precision, decimal format otherwise. (4)
'c' Single byte (accepts integer or single byte objects).  
'b' Bytes (any object that follows the buffer protocol or has __bytes__()). (5)
's' 's' is an alias for 'b' and should only be used for Python2/3 code bases. (6)
'a' Bytes (converts any Python object using repr(obj).encode('ascii','backslashreplace)). (5)
'r' 'r' is an alias for 'a' and should only be used for Python2/3 code bases. (7)
'%' No argument is converted, results in a '%' character in the result.  

注释:

  1. The alternate form causes a leading octal specifier ('0o') to be inserted before the first digit.

  2. 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.

  3. 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.

  4. 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.

  5. If precision is N, the output is truncated to N characters.

  6. b'%s' is deprecated, but will not be removed during the 3.x series.

  7. b'%r' is deprecated, but will not be removed during the 3.x series.

  8. See PEP 237.

注解

The bytearray version of this method does not operate in place - it always produces a new object, even if no changes were made.

参见

PEP 461 - Adding % formatting to bytes and bytearray

3.5 新版功能.

Memory Views

memoryview objects allow Python code to access the internal data of an object that supports the buffer protocol without copying.

class memoryview(obj)

Create a memoryview that references obj. obj must support the buffer protocol. Built-in objects that support the buffer protocol include bytes and bytearray.

A memoryview has the notion of an element, which is the atomic memory unit handled by the originating object obj. For many simple types such as bytes and bytearray, an element is a single byte, but other types such as array.array may have bigger elements.

len(view) is equal to the length of tolist. If view.ndim = 0, the length is 1. If view.ndim = 1, the length is equal to the number of elements in the view. For higher dimensions, the length is equal to the length of the nested list representation of the view. 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 the struct module, indexing with an integer or a tuple of integers is also supported and returns a single element with the correct type. One-dimensional memoryviews can be indexed with an integer or a one-integer tuple. Multi-dimensional memoryviews can be indexed with tuples of exactly ndim integers where ndim is the number of dimensions. Zero-dimensional memoryviews can be indexed with the empty tuple.

Here is an example with a non-byte format:

>>> import array
>>> 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

在 3.3 版更改: One-dimensional memoryviews can now be sliced. One-dimensional memoryviews with formats 'B', 'b' or 'c' are now hashable.

在 3.4 版更改: memoryview is now registered automatically with collections.abc.Sequence

在 3.5 版更改: 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 by tolist(), v and w are equal if v.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 imply v == w for memoryview objects.

在 3.3 版更改: Previous versions compared the raw memory disregarding the item format and the logical array structure.

tobytes(order=None)

Return the data in the buffer as a bytestring. This is equivalent to calling the bytes constructor on the memoryview.

>>> m = memoryview(b"abc")
>>> m.tobytes()
b'abc'
>>> bytes(m)
b'abc'

For non-contiguous arrays the result is equal to the flattened list representation with all elements converted to bytes. tobytes() supports all format strings, including those that are not in struct module syntax.

3.8 新版功能: 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()

Return a string object containing two hexadecimal digits for each byte in the buffer.

>>> m = memoryview(b"abc")
>>> m.hex()
'616263'

3.5 新版功能.

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]

在 3.3 版更改: tolist() now supports all single character native formats in struct module syntax as well as multi-dimensional representations.

toreadonly()

Return a readonly version of the memoryview object. The original memoryview object is unchanged.

>>> m = memoryview(bytearray(b'abc'))
>>> mm = m.toreadonly()
>>> mm.tolist()
[89, 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]

3.8 新版功能.

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 (except release() 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

3.2 新版功能.

cast(format[, shape])

Cast a memoryview to a new format or shape. shape defaults to [byte_length//new_itemsize], which means that the result view will be one-dimensional. The return value is a new memoryview, but the buffer itself is not copied. Supported casts are 1D -> C-contiguous and C-contiguous -> 1D.

The destination format is restricted to a single element native format in struct syntax. One of the formats must be a byte format ('B', 'b' or 'c'). The byte length of the result must be the same as the original length.

Cast 1D/long to 1D/unsigned bytes:

>>> import array
>>> a = array.array('l', [1,2,3])
>>> x = memoryview(a)
>>> x.format
'l'
>>> x.itemsize
8
>>> len(x)
3
>>> x.nbytes
24
>>> y = x.cast('B')
>>> y.format
'B'
>>> y.itemsize
1
>>> len(y)
24
>>> y.nbytes
24

Cast 1D/unsigned bytes to 1D/char:

>>> b = bytearray(b'zyz')
>>> x = memoryview(b)
>>> x[0] = b'a'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: memoryview: invalid value for format "B"
>>> y = x.cast('c')
>>> y[0] = b'a'
>>> b
bytearray(b'ayz')

Cast 1D/bytes to 3D/ints to 1D/signed char:

>>> import struct
>>> buf = struct.pack("i"*12, *list(range(12)))
>>> x = memoryview(buf)
>>> y = x.cast('i', shape=[2,2,3])
>>> y.tolist()
[[[0, 1, 2], [3, 4, 5]], [[6, 7, 8], [9, 10, 11]]]
>>> y.format
'i'
>>> y.itemsize
4
>>> len(y)
2
>>> y.nbytes
48
>>> z = y.cast('b')
>>> z.format
'b'
>>> z.itemsize
1
>>> len(z)
48
>>> z.nbytes
48

Cast 1D/unsigned char 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]]

3.3 新版功能.

在 3.5 版更改: 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

3.3 新版功能.

nbytes

nbytes == product(shape) * itemsize == len(m.tobytes()). This is the amount of space in bytes that the array would use in a contiguous representation. It is not necessarily equal to len(m):

>>> import array
>>> 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

3.3 新版功能.

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.

在 3.3 版更改: format 'B' is now handled according to the struct module syntax. This means that memoryview(b'abc')[0] == b'abc'[0] == 97.

itemsize

The size in bytes of each element of the memoryview:

>>> import array, struct
>>> 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.

在 3.3 版更改: 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.

在 3.3 版更改: 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.

3.3 新版功能.

f_contiguous

A bool indicating whether the memory is Fortran contiguous.

3.3 新版功能.

contiguous

A bool indicating whether the memory is contiguous.

3.3 新版功能.

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.

Instances of set and frozenset 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(), and symmetric_difference(), issubset(), and issuperset() methods will accept any iterable as an argument. In contrast, their operator based counterparts require their arguments to be sets. This precludes error-prone constructions like set('abc') & 'cbs' in favor of the more readable set('abc').intersection('cbs').

Both set and frozenset support set to set comparisons. Two sets are equal if and only if every element of each set is contained in the other (each is a subset of the other). A set is less than another set if and only if the first set is a proper subset of the second set (is a subset, but is not equal). A set is greater than another set if and only if the first set is a proper superset of the second set (is a superset, but is not equal).

Instances of set are compared to instances of frozenset based on their members. For example, set('abc') == frozenset('abc') returns True and so does set('abc') in set([frozenset('abc')]).

The subset and equality comparisons do not generalize to a total ordering function. For example, any two nonempty disjoint sets are not equal and are not subsets of each other, so all of the following return False: a<b, a==b, or a>b.

Since sets only define partial ordering (subset relationships), the output of the list.sort() method is undefined for lists of sets.

Set elements, like dictionary keys, must be hashable.

Binary operations that mix set instances with frozenset return the type of the first operand. For example: frozenset('ab') | set('bc') returns an instance of frozenset.

The following table lists operations available for set that do not apply to immutable instances of frozenset:

update(*others)
set |= other | ...

Update the set, adding elements from all others.

intersection_update(*others)
set &= other & ...

Update the set, keeping only elements found in it and all others.

difference_update(*others)
set -= other | ...

Update the set, removing elements found in others.

symmetric_difference_update(other)
set ^= other

Update the set, keeping only elements found in either set, but not in both.

add(elem)

Add element elem to the set.

remove(elem)

Remove element elem from the set. Raises KeyError if elem is not contained in the set.

discard(elem)

Remove element elem from the set if it is present.

pop()

Remove and return an arbitrary element from the set. Raises KeyError if the set is empty.

clear()

Remove all elements from the set.

Note, the non-operator versions of the update(), intersection_update(), difference_update(), and symmetric_difference_update() methods will accept any iterable as an argument.

Note, the elem argument to the __contains__(), remove(), and discard() methods may be a set. To support searching for an equivalent frozenset, a temporary one is created from elem.

Mapping Types --- dict

A mapping object maps hashable values to arbitrary objects. Mappings are mutable objects. There is currently only one standard mapping type, the dictionary. (For other containers see the built-in list, set, and tuple classes, and the collections module.)

A dictionary's keys are almost arbitrary values. Values that are not hashable, that is, values containing lists, dictionaries or other mutable types (that are compared by value rather than by object identity) may not be used as keys. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (such as 1 and 1.0) then they can be used interchangeably to index the same dictionary entry. (Note however, that since computers store floating-point numbers as approximations it is usually unwise to use them as dictionary keys.)

Dictionaries can be created by placing a comma-separated list of key: value pairs within braces, for example: {'jack': 4098, 'sjoerd': 4127} or {4098: 'jack', 4127: 'sjoerd'}, or by the dict constructor.

class dict(**kwarg)
class dict(mapping, **kwarg)
class dict(iterable, **kwarg)

Return a new dictionary initialized from an optional positional argument and a possibly empty set of keyword arguments.

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})
>>> a == b == c == d == e
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):

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, the d[key] operation calls that method with the key key as argument. The d[key] operation then returns or raises whatever is returned or raised by the __missing__(key) call. No other operations or methods invoke __missing__(). If __missing__() is not defined, KeyError is raised. __missing__() must be a method; it cannot be an instance variable:

>>> class Counter(dict):
...     def __missing__(self, key):
...         return 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 by collections.defaultdict.

d[key] = value

Set d[key] to value.

del d[key]

Remove d[key] from d. Raises a KeyError if key is not in the map.

key in d

Return True if d has a key key, else False.

key not in d

Equivalent to not key in d.

iter(d)

Return an iterator over the keys of the dictionary. This is a shortcut for iter(d.keys()).

clear()

Remove all items from the dictionary.

copy()

Return a shallow copy of the dictionary.

classmethod fromkeys(iterable[, value])

Create a new dictionary with keys from iterable and values set to value.

fromkeys() is a class method that returns a new dictionary. value defaults to None.

get(key[, default])

Return the value for key if key is in the dictionary, else default. If default is not given, it defaults to None, so that this method never raises a KeyError.

items()

Return a new view of the dictionary's items ((key, value) pairs). See the documentation of view objects.

keys()

Return a new view of the dictionary's keys. See the documentation of view objects.

pop(key[, 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, calling popitem() raises a KeyError.

在 3.7 版更改: 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()).

setdefault(key[, default])

如果字典存在键 key ,返回它的值。如果不存在,插入值为 default 的键 key ,并返回 defaultdefault 默认为 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.

Dictionaries compare equal if and only if they have the same (key, value) pairs. Order comparisons ('<', '<=', '>=', '>') raise TypeError.

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}

在 3.7 版更改: 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)]

在 3.8 版更改: Dictionaries are now reversible.

参见

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 using zip(): pairs = zip(d.values(), d.keys()). Another way to create the same list is pairs = [(v, k) for (k, v) in d.items()].

Iterating views while adding or deleting entries in the dictionary may raise a RuntimeError or fail to iterate over all entries.

在 3.7 版更改: 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.

在 3.8 版更改: Dictionary views are now reversible.

Keys views are set-like since their entries are unique and hashable. If all values are hashable, so that (key, value) pairs are unique and hashable, then the items view is also set-like. (Values views are not treated as set-like since the entries are generally not unique.) For set-like views, all of the operations defined for the abstract base class collections.abc.Set are available (for example, ==, <, or ^).

An example of dictionary view usage:

>>> dishes = {'eggs': 2, 'sausage': 1, 'bacon': 1, 'spam': 500}
>>> keys = dishes.keys()
>>> values = dishes.values()

>>> # iteration
>>> n = 0
>>> for val in values:
...     n += val
>>> print(n)
504

>>> # keys and values are iterated over in the same order (insertion order)
>>> list(keys)
['eggs', 'sausage', 'bacon', 'spam']
>>> list(values)
[2, 1, 1, 500]

>>> # view objects are dynamic and reflect dict changes
>>> del dishes['eggs']
>>> del dishes['sausage']
>>> list(keys)
['bacon', 'spam']

>>> # set operations
>>> keys & {'eggs', 'bacon', 'salad'}
{'bacon'}
>>> keys ^ {'sausage', 'juice'}
{'juice', 'sausage', 'bacon', 'spam'}

Context Manager Types

Python's with statement supports the concept of a runtime context defined by a context manager. This is implemented using a pair of methods that allow user-defined classes to define a runtime context that is entered before the statement body is executed and exited when the statement ends:

contextmanager.__enter__()

Enter the runtime context and return either this object or another object related to the runtime context. The value returned by this method is bound to the identifier in the as clause of with statements using this context manager.

An example of a context manager that returns itself is a file object. File objects return themselves from __enter__() to allow open() to be used as the context expression in a with statement.

An example of a context manager that returns a related object is the one returned by decimal.localcontext(). These managers set the active decimal context to a copy of the original decimal context and then return the copy. This allows changes to be made to the current decimal context in the body of the with statement without affecting code outside the with statement.

contextmanager.__exit__(exc_type, exc_val, exc_tb)

Exit the runtime context and return a Boolean flag indicating if any exception that occurred should be suppressed. If an exception occurred while executing the body of the with statement, the arguments contain the exception type, value and traceback information. Otherwise, all three arguments are None.

Returning a true value from this method will cause the with statement to suppress the exception and continue execution with the statement immediately following the with statement. Otherwise the exception continues propagating after this method has finished executing. Exceptions that occur during execution of this method will replace any exception that occurred in the body of the with 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.

Other Built-in Types

The interpreter supports several other kinds of objects. Most of these support only one or two operations.

模块

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 对象、值与类型 and 类定义 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 函数定义 for more information.

Methods

Methods are functions that are called using the attribute notation. There are two flavors: built-in methods (such as append() on lists) and class instance methods. Built-in methods are described with the types that support them.

If you access a method (a function defined in a class namespace) through an instance, you get a special object: a bound method (also called instance method) object. When called, it will add the self argument to the argument list. Bound methods have two special read-only attributes: m.__self__ is the object on which the method operates, and m.__func__ is the function implementing the method. Calling m(arg-1, arg-2, ..., arg-n) is completely equivalent to calling m.__func__(m.__self__, arg-1, arg-2, ..., arg-n).

Like function objects, bound method objects support getting arbitrary attributes. However, since method attributes are actually stored on the underlying function object (meth.__func__), setting method attributes on bound methods is disallowed. Attempting to set an attribute on a method results in an AttributeError being raised. In order to set a method attribute, you need to explicitly set it on the underlying function object:

>>> class C:
...     def method(self):
...         pass
...
>>> c = C()
>>> c.method.whoami = 'my name is method'  # can't set on the method
Traceback (most recent call last):
  File "<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 标准类型层级结构 for more information.

代码对象

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.

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 标准类型层级结构 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 切片). 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 比较运算 for more information. There is exactly one NotImplemented object. type(NotImplemented)() produces the singleton instance.

It is written as NotImplemented.

Boolean Values

Boolean values are the two constant objects False and True. They are used to represent truth values (although other values can also be considered false or true). In numeric contexts (for example when used as the argument to an arithmetic operator), they behave like the integers 0 and 1, respectively. The built-in function bool() can be used to convert any value to a Boolean, if the value can be interpreted as a truth value (see section 逻辑值检测 above).

They are written as False and True, respectively.

Internal Objects

See 标准类型层级结构 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.

object.__dict__

A dictionary or other mapping object used to store an object's (writable) attributes.

instance.__class__

The class to which a class instance belongs.

class.__bases__

The tuple of base classes of a class object.

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.

3.3 新版功能.

class.__mro__

This attribute is a tuple of classes that are considered when looking for base classes during method resolution.

class.mro()

This method can be overridden by a metaclass to customize the method resolution order for its instances. It is called at class instantiation, and its result is stored in __mro__.

class.__subclasses__()

Each class keeps a list of weak references to its immediate subclasses. This method returns a list of all those references still alive. Example:

>>> int.__subclasses__()
[<class 'bool'>]

脚注

[1]Additional information on these special methods may be found in the Python Reference Manual (基本定制).
[2]As a consequence, the list [1, 2] is considered equal to [1.0, 2.0], and similarly for tuples.
[3]They must have since the parser can't tell the type of the operands.
[4](1, 2, 3, 4) Cased characters are those with general category property being one of "Lu" (Letter, uppercase), "Ll" (Letter, lowercase), or "Lt" (Letter, titlecase).
[5](1, 2) To format only a tuple you should therefore provide a singleton tuple whose only element is the tuple to be formatted.