5. 内置类型

以下部分描述了解释器中内置的标准类型。

注解

Historically (until release 2.2), Python’s built-in types have differed from user-defined types because it was not possible to use the built-in types as the basis for object-oriented inheritance. This limitation no longer exists.

The principal built-in types are numerics, sequences, mappings, files, classes, instances and exceptions.

Some operations are supported by several object types; in particular, practically all objects can be compared, 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.

5.1. 逻辑值检测

Any object can be tested for truth value, for use in an if or while condition or as operand of the Boolean operations below. The following values are considered false:

• None

• False

• zero of any numeric type, for example, 0, 0L, 0.0, 0j.

• any empty sequence, for example, '', (), [].

• any empty mapping, for example, {}.

• instances of user-defined classes, if the class defines a __nonzero__() or __len__() method, when that method returns the integer zero or bool value False. [1]

All other values are considered true — so objects of many types are always true.

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

5.2. Boolean Operations — 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) 而 a == not b 会引发语法错误。

5.3. 比较

Comparison operations are supported by all objects. They all have the same priority (which is higher than that of the Boolean operations). Comparisons can be chained arbitrarily; for example, x < y <= z is equivalent to x < y and y <= z, except that y is evaluated only once (but in both cases z is not evaluated at all when x < y is found to be false).

此表格汇总了比较运算:

运算	含义	注释
<	严格小于
<=	小于或等于
>	严格大于
>=	大于或等于
==	等于
!=	不等于	(1)
is	对象标识
is not	否定的对象标识

注释:

1. != can also be written <>, but this is an obsolete usage kept for backwards compatibility only. New code should always use !=.

Objects of different types, except different numeric types and different string types, never compare equal; such objects are ordered consistently but arbitrarily (so that sorting a heterogeneous array yields a consistent result). Furthermore, some types (for example, file objects) support only a degenerate notion of comparison where any two objects of that type are unequal. Again, such objects are ordered arbitrarily but consistently. The <, <=, > and >= operators will raise a TypeError exception when any operand is a complex number.

Non-identical instances of a class normally compare as non-equal unless the class defines the __eq__() method or the __cmp__() method.

Instances of a class cannot be ordered with respect to other instances of the same class, or other types of object, unless the class defines either enough of the rich comparison methods (__lt__(), __le__(), __gt__(), and __ge__()) or the __cmp__() method.

CPython implementation detail: Objects of different types except numbers are ordered by their type names; objects of the same types that don’t support proper comparison are ordered by their address.

Two more operations with the same syntactic priority, in and not in, are supported only by sequence types (below).

5.4. Numeric Types — int, float, long, complex

There are four distinct numeric types: plain integers, long integers, floating point numbers, and complex numbers. In addition, Booleans are a subtype of plain integers. Plain integers (also just called integers) are implemented using long in C, which gives them at least 32 bits of precision (sys.maxint is always set to the maximum plain integer value for the current platform, the minimum value is -sys.maxint - 1). Long 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 additional numeric types, fractions that hold rationals, and decimal that hold floating-point numbers with user-definable precision.)

Numbers are created by numeric literals or as the result of built-in functions and operators. Unadorned integer literals (including binary, hex, and octal numbers) yield plain integers unless the value they denote is too large to be represented as a plain integer, in which case they yield a long integer. Integer literals with an 'L' or 'l' suffix yield long integers ('L' is preferred because 1l looks too much like eleven!). Numeric literals containing a decimal point or an exponent sign yield floating point numbers. Appending 'j' or 'J' to a numeric literal yields an imaginary number (a complex number with a zero real part) which you can add to an integer or float to get a complex number with real and imaginary parts.

Python fully supports mixed arithmetic: when a binary arithmetic operator has operands of different numeric types, the operand with the “narrower” type is widened to that of the other, where plain integer is narrower than long integer is narrower than floating point is narrower than complex. Comparisons between numbers of mixed type use the same rule. [2] The constructors int(), long(), float(), and complex() can be used to produce numbers of a specific type.

All built-in numeric types support the following operations. See 幂运算符 and later sections for the operators’ priorities.

运算	结果	注释
x + y	x 和 y 的和
x - y	x 和 y 的差
x * y	x 和 y 的乘积
x / y	x 和 y 的商	(1)
x // y	(floored) quotient of x and y	(4)(5)
x % y	remainder of x / y	(4)
-x	x 取反
+x	x 不变
abs(x)	x 的绝对值或大小	(3)
int(x)	将 x 转换为整数	(2)
long(x)	x converted to long integer	(2)
float(x)	将 x 转换为浮点数	(6)
complex(re,im)	一个带有实部 re 和虚部 im 的复数。im 默认为0。
c.conjugate()	conjugate of the complex number c. (Identity on real numbers)
divmod(x, y)	(x // y, x % y)	(3)(4)
pow(x, y)	x 的 y 次幂	(3)(7)
x ** y	x 的 y 次幂	(7)

注释:

1. For (plain or long) integer division, the result is an integer. The result is always rounded towards minus infinity: 1/2 is 0, (-1)/2 is -1, 1/(-2) is -1, and (-1)/(-2) is 0. Note that the result is a long integer if either operand is a long integer, regardless of the numeric value.

2. Conversion from floats using int() or long() truncates toward zero like the related function, math.trunc(). Use the function math.floor() to round downward and math.ceil() to round upward.

3. See 内置函数 for a full description.

4. 2.3 版后已移除: The floor division operator, the modulo operator, and the divmod() function are no longer defined for complex numbers. Instead, convert to a floating point number using the abs() function if appropriate.

5. Also referred to as integer division. The resultant value is a whole integer, though the result’s type is not necessarily int.

6. 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。

   2.6 新版功能.

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

All numbers.Real types (int, long, and float) also include the following operations:

运算	结果
math.trunc(x)	x 截断为 Integral
round(x[, n])	x rounded to n digits, rounding ties away from zero. If n is omitted, it defaults to 0.
math.floor(x)	the greatest integer as a float <= x
math.ceil(x)	the least integer as a float >= x

5.4.1. 整数类型的按位运算

Bitwise operations only make sense for integers. Negative numbers are treated as their 2’s complement value (this assumes a sufficiently large number of bits that no overflow occurs during the operation).

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	x 和 y 按位 或
x ^ y	x 和 y 按位 异或
x & y	x 和 y 按位 与
x << n	x 左移 n 位	(1)(2)
x >> n	x 右移 n 位	(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. A left shift by n bits is equivalent to multiplication by pow(2, n). A long integer is returned if the result exceeds the range of plain integers.
3. A right shift by n bits is equivalent to division by pow(2, n).

5.4.2. 整数类型的附加方法

The integer types implement the numbers.Integral abstract base class. In addition, they provide one more method:

int.bit_length()

long.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

2.7 新版功能.

5.4.3. 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。

2.6 新版功能.

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

2.6 新版功能.

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。

2.6 新版功能.

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。

2.6 新版功能.

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 + 或 -，integer 和 fraction 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**10 即 3740.0:

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

对 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'

5.5. 迭代器类型

2.2 新版功能.

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 for 和 in 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。

The intention of the protocol is that once an iterator’s next() method raises StopIteration, it will continue to do so on subsequent calls. Implementations that do not obey this property are deemed broken. (This constraint was added in Python 2.3; in Python 2.2, various iterators are broken according to this rule.)

5.5.1. 生成器类型

Python’s generators provide a convenient way to implement the iterator protocol. If a container object’s __iter__() method is implemented as a generator, it will automatically return an iterator object (technically, a generator object) supplying the __iter__() and next() methods. More information about generators can be found in the documentation for the yield expression.

5.6. Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange

There are seven sequence types: strings, Unicode strings, lists, tuples, bytearrays, buffers, and xrange objects.

For other containers see the built in dict and set classes, and the collections module.

String literals are written in single or double quotes: 'xyzzy', "frobozz". See String literals for more about string literals. Unicode strings are much like strings, but are specified in the syntax using a preceding 'u' character: u'abc', u"def". In addition to the functionality described here, there are also string-specific methods described in the 字符串的方法 section. Lists are constructed with square brackets, separating items with commas: [a, b, c]. Tuples are constructed by the comma operator (not within square brackets), with or without enclosing parentheses, but an empty tuple must have the enclosing parentheses, such as a, b, c or (). A single item tuple must have a trailing comma, such as (d,).

Bytearray objects are created with the built-in function bytearray().

Buffer objects are not directly supported by Python syntax, but can be created by calling the built-in function buffer(). They don’t support concatenation or repetition.

Objects of type xrange are similar to buffers in that there is no specific syntax to create them, but they are created using the xrange() function. They don’t support slicing, concatenation or repetition, and using in, not in, min() or max() on them is inefficient.

Most sequence types support the following operations. The in and not in operations have the same priorities as the comparison operations. The + and * operations have the same priority as the corresponding numeric operations. [3] Additional methods are provided for 可变序列类型.

This table lists the sequence operations sorted in ascending priority. In the table, s and t are sequences of the same type; n, i and j are integers:

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	s 与 t 相拼接	(6)
s * n, n * s	相当于 s 与自身进行 n 次拼接	(2)
s[i]	s 的第 i 项，起始为 0	(3)
s[i:j]	s 从 i 到 j 的切片	(3)(4)
s[i:j:k]	s 从 i 到 j 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)	index of the first occurrence of x in s
s.count(x)	x 在 s 中出现的总次数

Sequence types also support comparisons. In particular, tuples and lists are compared lexicographically by comparing corresponding elements. This means that to compare equal, every element must compare equal and the two sequences must be of the same type and have the same length. (For full details see 比较运算 in the language reference.)

注释:

1. When s is a string or Unicode string object the in and not in operations act like a substring test. In Python versions before 2.3, x had to be a string of length 1. In Python 2.3 and beyond, x may be a string of any length.

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]]
   

   进一步的解释可以在 FAQ 条目 How do I create a multidimensional list? 中查看。

3. 如果 i 或 j 为负值，则索引顺序是相对于序列 s 的末尾: 索引号会被替换为 len(s) + i 或 len(s) + j。 但要注意 -0 仍然为 0。

4. s 从 i 到 j 的切片被定义为所有满足 i <= k < j 的索引号 k 的项组成的序列。 如果 i 或 j 大于 len(s)，则使用 len(s)。 如果 i 被省略或为 None，则使用 0。 如果 j 被省略或为 None，则使用 len(s)。 如果 i 大于等于 j，则切片为空。

5. s 从 i 到 j 步长为 k 的切片被定义为所有满足 0 <= n < (j-i)/k 的索引号 x = i + n*k 的项组成的序列。 换句话说，索引号为 i, i+k, i+2*k, i+3*k，以此类推，当达到 j 时停止 (但一定不包括 j)。 当 k 为正值时，i 和 j 会被减至不大于 len(s)。 当 k 为负值时，i 和 j 会被减至不大于 len(s) - 1。 如果 i 或 j 被省略或为 None，它们会成为“终止”值 (是哪一端的终止值则取决于 k 的符号)。 请注意，k 不可为零。 如果 k 为 None，则当作 1 处理。

6. CPython implementation detail: If s and t are both strings, some Python implementations such as CPython can usually perform an in-place optimization for assignments of the form s = s + t or s += t. When applicable, this optimization makes quadratic run-time much less likely. This optimization is both version and implementation dependent. For performance sensitive code, it is preferable to use the str.join() method which assures consistent linear concatenation performance across versions and implementations.

   在 2.4 版更改: Formerly, string concatenation never occurred in-place.

5.6.1. 字符串的方法

Below are listed the string methods which both 8-bit strings and Unicode objects support. Some of them are also available on bytearray objects.

In addition, Python’s strings support the sequence type methods described in the Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange section. To output formatted strings use template strings or the % operator described in the String Formatting Operations section. Also, see the re module for string functions based on regular expressions.

str.capitalize()

返回原字符串的副本，其首个字符大写，其余为小写。

For 8-bit strings, this method is locale-dependent.

str.center(width[, fillchar])

Return centered in a string of length width. Padding is done using the specified fillchar (default is a space).

在 2.4 版更改: Support for the fillchar argument.

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

反回子字符串 sub 在 [start, end] 范围内非重叠出现的次数。 可选参数 start 与 end 会被解读为切片表示法。

str.decode([encoding[, errors]])

Decodes the string using the codec registered for encoding. encoding defaults to the default string encoding. errors may be given to set a different error handling scheme. The default is 'strict', meaning that encoding errors raise UnicodeError. Other possible values are 'ignore', 'replace' and any other name registered via codecs.register_error(), see section Codec Base Classes.

2.2 新版功能.

在 2.3 版更改: Support for other error handling schemes added.

在 2.7 版更改: 加入了对关键字参数的支持。

str.encode([encoding[, errors]])

Return an encoded version of the string. Default encoding is the current default string encoding. 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 Codec Base Classes. For a list of possible encodings, see section 标准编码.

2.0 新版功能.

在 2.3 版更改: Support for 'xmlcharrefreplace' and 'backslashreplace' and other error handling schemes added.

在 2.7 版更改: 加入了对关键字参数的支持。

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

如果字符串以指定的 suffix 结束返回 True，否则返回 False。 suffix 也可以为由多个供查找的后缀构成的元组。 如果有可选项 start，将从所指定位置开始检查。 如果有可选项 end，将在所指定位置停止比较。

在 2.5 版更改: Accept tuples as suffix.

str.expandtabs([tabsize])

返回字符串的副本，其中所有的制表符会由一个或多个空格替换，具体取决于当前列位置和给定的制表符宽度。 每 tabsize 个字符设为一个制表位（默认值 8 时设定的制表位在列 0, 8, 16 依次类推）。 要展开字符串，当前列将被设为零并逐一检查字符串中的每个字符。 如果字符为制表符 (\t)，则会在结果中插入一个或多个空格符，直到当前列等于下一个制表位。 （制表符本身不会被复制。） 如果字符为换行符 (\n) 或回车符 (\r)，它会被复制并将当前列重设为零。 任何其他字符会被不加修改地复制并将当前列加一，不论该字符在被打印时会如何显示。

>>> '01\t012\t0123\t01234'.expandtabs()
'01      012     0123    01234'
>>> '01\t012\t0123\t01234'.expandtabs(4)
'01  012 0123    01234'

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

返回子字符串 sub 在 s[start:end] 切片内被找到的最小索引。 可选参数 start 与 end 会被解读为切片表示法。 如果 sub 未被找到则返回 -1。

注解

find() 方法应该只在你需要知道 sub 所在位置时使用。 要检查 sub 是否为子字符串，请使用 in 操作符:

>>> 'Py' in 'Python'
True

str.format(*args, **kwargs)

执行字符串格式化操作。 调用此方法的字符串可以包含字符串字面值或者以花括号 {} 括起来的替换域。 每个替换域可以包含一个位置参数的数字索引，或者一个关键字参数的名称。 返回的字符串副本中每个替换域都会被替换为对应参数的字符串值。

>>> "The sum of 1 + 2 is {0}".format(1+2)
'The sum of 1 + 2 is 3'

请参阅 Format String Syntax 了解有关可以在格式字符串中指定的各种格式选项的说明。

This method of string formatting is the new standard in Python 3, and should be preferred to the % formatting described in String Formatting Operations in new code.

2.6 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.

For 8-bit strings, this method is locale-dependent.

str.isalpha()

Return true if all characters in the string are alphabetic and there is at least one character, false otherwise.

For 8-bit strings, this method is locale-dependent.

str.isdigit()

Return true if all characters in the string are digits and there is at least one character, false otherwise.

For 8-bit strings, this method is locale-dependent.

str.islower()

如果字符串中至少有一个区分大小写的字符 [4] 且此类字符均为小写则返回真值，否则返回假值。

For 8-bit strings, this method is locale-dependent.

str.isspace()

Return true if there are only whitespace characters in the string and there is at least one character, false otherwise.

For 8-bit strings, this method is locale-dependent.

str.istitle()

如果字符串中至少有一个字符且为标题字符串则返回真值，例如大写字符之后只能带非大写字符而小写字符必须有大写字符打头。 否则返回假值。

For 8-bit strings, this method is locale-dependent.

str.isupper()

如果字符串中至少有一个区分大小写的字符 [4] 具此类字符均为大写则返回真值，否则返回假值。

For 8-bit strings, this method is locale-dependent.

str.join(iterable)

Return a string which is the concatenation of the strings in iterable. If there is any Unicode object in iterable, return a Unicode instead. A TypeError will be raised if there are any non-string or non Unicode object values in iterable. 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 a space). The original string is returned if width is less than or equal to len(s).

在 2.4 版更改: Support for the fillchar argument.

str.lower()

返回原字符串的副本，其所有区分大小写的字符 [4] 均转换为小写。

For 8-bit strings, this method is locale-dependent.

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'

在 2.2.2 版更改: Support for the chars argument.

str.partition(sep)

在 sep 首次出现的位置拆分字符串，返回一个 3 元组，其中包含分隔符之前的部分、分隔符本身，以及分隔符之后的部分。 如果分隔符未找到，则返回的 3 元组中包含字符本身以及两个空字符串。

2.5 新版功能.

str.replace(old, new[, count])

返回字符串的副本，其中出现的所有子字符串 old 都将被替换为 new。 如果给出了可选参数 count，则只替换前 count 次出现。

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

返回子字符串 sub 在字符串内被找到的最大（最右）索引，这样 sub 将包含在 s[start:end] 当中。 可选参数 start 与 end 会被解读为切片表示法。 如果未找到则返回 -1。

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

类似于 rfind()，但在子字符串 sub 未找到时会引发 ValueError。

str.rjust(width[, fillchar])

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

在 2.4 版更改: Support for the fillchar argument.

str.rpartition(sep)

在 sep 最后一次出现的位置拆分字符串，返回一个 3 元组，其中包含分隔符之前的部分、分隔符本身，以及分隔符之后的部分。 如果分隔符未找到，则返回的 3 元组中包含两个空字符串以及字符串本身。

2.5 新版功能.

str.rsplit([sep[, maxsplit]])

返回一个由字符串内单词组成的列表，使用 sep 作为分隔字符串。 如果给出了 maxsplit，则最多进行 maxsplit 次拆分，从 最右边 开始。 如果 sep 未指定或为 None，任何空白字符串都会被作为分隔符。 除了从右边开始拆分，rsplit() 的其他行为都类似于下文所述的 split()。

2.4 新版功能.

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'

在 2.2.2 版更改: Support for the chars argument.

str.split([sep[, maxsplit]])

返回一个由字符串内单词组成的列表，使用 sep 作为分隔字符串。 如果给出了 maxsplit，则最多进行 maxsplit 次拆分（因此，列表最多会有 maxsplit+1 个元素）。 如果 maxsplit 未指定或为 -1，则不限制拆分次数（进行所有可能的拆分）。

如果给出了 sep，则连续的分隔符不会被组合在一起而是被视为分隔空字符串 (例如 '1,,2'.split(',') 将返回 ['1', '', '2'])。 sep 参数可能由多个字符组成 (例如 '1<>2<>3'.split('<>') 将返回 ['1', '2', '3'])。 使用指定的分隔符拆分空字符串将返回 ['']。

如果 sep 未指定或为 None，则会应用另一种拆分算法：连续的空格会被视为单个分隔符，其结果将不包含开头或末尾的空字符串，如果字符串包含前缀或后缀空格的话。 因此，使用 None 拆分空字符串或仅包含空格的字符串将返回 []。

For example, ' 1  2   3  '.split() returns ['1', '2', '3'], and '  1  2   3  '.split(None, 1) returns ['1', '2   3  '].

str.splitlines([keepends])

Return a list of the lines in the string, breaking at 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.

Python recognizes "\r", "\n", and "\r\n" as line boundaries for 8-bit strings.

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(True)
['ab c\n', '\n', 'de fg\r', 'kl\r\n']

不同于 split()，当给出了分隔字符串 sep 时，对于空字符串此方法将返回一个空列表，而末尾的换行不会令结果中增加额外的行:

>>> "".splitlines()
[]
>>> "One line\n".splitlines()
['One line']

作为比较，split('\n') 的结果为:

>>> ''.split('\n')
['']
>>> 'Two lines\n'.split('\n')
['Two lines', '']

unicode.splitlines([keepends])

Return a list of the lines in the string, like str.splitlines(). However, the Unicode method splits on the following line boundaries, which are a superset of the universal newlines recognized for 8-bit strings.

表示符	描述
\n	换行
\r	回车
\r\n	回车 + 换行
\v 或 \x0b	行制表符
\f 或 \x0c	换表单
\x1c	文件分隔符
\x1d	组分隔符
\x1e	记录分隔符
\x85	下一行 (C1 控制码)
\u2028	行分隔符
\u2029	段分隔符

在 2.7 版更改: \v 和 \f 被添加到行边界列表

str.startswith(prefix[, start[, end]])

如果字符串以指定的 prefix 开始则返回 True，否则返回 False。 prefix 也可以为由多个供查找的前缀构成的元组。 如果有可选项 start，将从所指定位置开始检查。 如果有可选项 end，将在所指定位置停止比较。

在 2.5 版更改: Accept tuples as prefix.

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'

在 2.2.2 版更改: Support for the chars argument.

str.swapcase()

Return a copy of the string with uppercase characters converted to lowercase and vice versa.

For 8-bit strings, this method is locale-dependent.

str.title()

返回原字符串的标题版本，其中每个单词第一个字母为大写，其余字母为小写。

该算法使用一种简单的与语言无关的定义，将连续的字母组合视为单词。 该定义在多数情况下都很有效，但它也意味着代表缩写形式与所有格的撇号也会成为单词边界，这可能导致不希望的结果:

>>> "they're bill's friends from the UK".title()
"They'Re Bill'S Friends From The Uk"

可以使用正则表达式来构建针对撇号的特别处理:

>>> 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."

For 8-bit strings, this method is locale-dependent.

str.translate(table[, deletechars])

Return a copy of the string where all characters occurring in the optional argument deletechars are removed, and the remaining characters have been mapped through the given translation table, which must be a string of length 256.

You can use the maketrans() helper function in the string module to create a translation table. For string objects, set the table argument to None for translations that only delete characters:

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

2.6 新版功能: Support for a None table argument.

For Unicode objects, the translate() method does not accept the optional deletechars argument. Instead, it returns a copy of the s where all characters have been mapped through the given translation table which must be a mapping of Unicode ordinals to Unicode ordinals, Unicode strings or None. Unmapped characters are left untouched. Characters mapped to None are deleted. Note, a more flexible approach is to create a custom character mapping codec using the codecs module (see encodings.cp1251 for an example).

str.upper()

返回原字符串的副本，其中所有区分大小写的字符 [4] 均转换为大写。 请注意如果 s 包含不区分大小写的字符或者如果结果字符的 Unicode 类别不是 “Lu” (Letter, uppercase) 而是 “Lt” (Letter, titlecase) 则 s.upper().isupper() 有可能为 False。

For 8-bit strings, this method is locale-dependent.

str.zfill(width)

Return the numeric string left filled with zeros in a string of length width. A sign prefix is handled correctly. The original string is returned if width is less than or equal to len(s).

2.2.2 新版功能.

The following methods are present only on unicode objects:

unicode.isnumeric()

Return True if there are only numeric characters in S, 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.

unicode.isdecimal()

Return True if there are only decimal characters in S, False otherwise. Decimal characters include digit characters, and all characters that can be used to form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.

5.6.2. String Formatting Operations

String and Unicode 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 or Unicode object), % conversion specifications in format are replaced with zero or more elements of values. The effect is similar to the using sprintf() in the C language. If format is a Unicode object, or if any of the objects being converted using the %s conversion are Unicode objects, the result will also be a Unicode object.

如果 format 要求一个单独参数，则 values 可以为一个非元组对象。 [5] 否则的话，values 必须或者是一个包含项数与格式字符串中指定的转换符项数相同的元组，或者是一个单独映射对象（例如字典）。

转换标记符包含两个或更多字符并具有以下组成，且必须遵循此处规定的顺序：

1. '%' 字符，用于标记转换符的起始。
2. 映射键（可选），由加圆括号的字符序列组成 (例如 (somename))。
3. 转换旗标（可选），用于影响某些转换类型的结果。
4. 最小字段宽度（可选）。 如果指定为 '*' (星号)，则实际宽度会从 values 元组的下一元素中读取，要转换的对象则为最小字段宽度和可选的精度之后的元素。
5. Precision (optional), given as a '.' (dot) followed by the precision. If specified as '*' (an asterisk), the actual width is read from the next element of the tuple in values, and the value to convert comes after the precision.
6. 长度修饰符（可选）。
7. 转换类型。

当右边的参数为一个字典（或其他映射类型）时，字符串中的格式 必须 包含加圆括号的映射键，对应 '%' 字符之后字典中的每一项。 映射键将从映射中选取要格式化的值。 例如：

>>> print '%(language)s has %(number)03d quote types.' % \
...       {"language": "Python", "number": 2}
Python has 002 quote types.

在此情况下格式中不能出现 * 标记符（因其需要一个序列类的参数列表）。

转换旗标为：

标志	含义
'#'	值的转换将使用“替代形式”（具体定义见下文）。
'0'	转换将为数字值填充零字符。
'-'	转换值将靠左对齐（如果同时给出 '0' 转换，则会覆盖后者）。
' '	(空格) 符号位转换产生的正数（或空字符串）前将留出一个空格。
'+'	符号字符 ('+' 或 '-') 将显示于转换结果的开头（会覆盖 “空格” 旗标）。

可以给出长度修饰符 (h, l 或 L)，但会被忽略，因为对 Python 来说没有必要 – 所以 %ld 等价于 %d。

转换类型为：

转换符	含义	注释
'd'	有符号十进制整数。
'i'	有符号十进制整数。
'o'	有符号八进制数。	(1)
'u'	过时类型 – 等价于 'd'。	(7)
'x'	有符号十六进制数（小写）。	(2)
'X'	有符号十六进制数（大写）。	(2)
'e'	浮点指数格式（小写）。	(3)
'E'	浮点指数格式（大写）。	(3)
'f'	浮点十进制格式。	(3)
'F'	浮点十进制格式。	(3)
'g'	浮点格式。 如果指数小于 -4 或不小于精度则使用小写指数格式，否则使用十进制格式。	(4)
'G'	浮点格式。 如果指数小于 -4 或不小于精度则使用大写指数格式，否则使用十进制格式。	(4)
'c'	单个字符（接受整数或单个字符的字符串）。
'r'	String (converts any Python object using repr()).	(5)
's'	字符串（使用 str() 转换任何 Python 对象）。	(6)
'%'	不转换参数，在结果中输出一个 '%' 字符。

注释:

1. The alternate form causes a leading zero ('0') to be inserted between left-hand padding and the formatting of the number if the leading character of the result is not already a zero.

2. 此替代形式会在第一个数码之前插入 '0x' 或 '0X' 前缀（取决于是使用 'x' 还是 'X' 格式）。

3. 此替代形式总是会在结果中包含一个小数点，即使其后并没有数码。

   小数点后的数码位数由精度决定，默认为 6。

4. 此替代形式总是会在结果中包含一个小数点，末尾各位的零不会如其他情况下那样被移除。

   小数点前后的有效数码位数由精度决定，默认为 6。

5. The %r conversion was added in Python 2.0.

   The precision determines the maximal number of characters used.

6. If the object or format provided is a unicode string, the resulting string will also be unicode.

   The precision determines the maximal number of characters used.

7. 参见 PEP 237。

由于 Python 字符串显式指明长度，%s 转换不会将 '\0' 视为字符串的结束。

在 2.7 版更改: 绝对值超过 1e50 的 %f 转换不会再被替换为 %g 转换。

Additional string operations are defined in standard modules string and re.

5.6.3. XRange Type

The xrange type is an immutable sequence which is commonly used for looping. The advantage of the xrange type is that an xrange object will always take the same amount of memory, no matter the size of the range it represents. There are no consistent performance advantages.

XRange objects have very little behavior: they only support indexing, iteration, and the len() function.

5.6.4. 可变序列类型

List and bytearray objects support additional operations that allow in-place modification of the object. Other mutable sequence types (when added to the language) should also support these operations. Strings and tuples are immutable sequence types: such objects cannot be modified once created. The following operations are defined on mutable sequence types (where x is an arbitrary object):

运算	结果	注释
s[i] = x	将 s 的第 i 项替换为 x
s[i:j] = t	将 s 从 i 到 j 的切片替换为可迭代对象 t 的内容
del s[i:j]	等同于 s[i:j] = []
s[i:j:k] = t	将 s[i:j:k] 的元素替换为 t 的元素	(1)
del s[i:j:k]	从列表中移除 s[i:j:k] 的元素
s.append(x)	same as s[len(s):len(s)] = [x]	(2)
s.extend(t) 或 s += t	for the most part the same as s[len(s):len(s)] = t	(3)
s *= n	使用 s 的内容重复 n 次来对其进行更新	(11)
s.count(x)	return number of i’s for which s[i] == x
s.index(x[, i[, j]])	return smallest k such that s[k] == x and i <= k < j	(4)
s.insert(i, x)	same as s[i:i] = [x]	(5)
s.pop([i])	same as x = s[i]; del s[i]; return x	(6)
s.remove(x)	same as del s[s.index(x)]	(4)
s.reverse()	就地将列表中的元素逆序。	(7)
s.sort([cmp[, key[, reverse]]])	sort the items of s in place	(7)(8)(9)(10)

注释:

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

2. The C implementation of Python has historically accepted multiple parameters and implicitly joined them into a tuple; this no longer works in Python 2.0. Use of this misfeature has been deprecated since Python 1.4.

3. t can be any iterable object.

4. Raises ValueError when x is not found in s. When a negative index is passed as the second or third parameter to the index() method, the list length is added, as for slice indices. If it is still negative, it is truncated to zero, as for slice indices.

   在 2.3 版更改: Previously, index() didn’t have arguments for specifying start and stop positions.

5. When a negative index is passed as the first parameter to the insert() method, the list length is added, as for slice indices. If it is still negative, it is truncated to zero, as for slice indices.

   在 2.3 版更改: Previously, all negative indices were truncated to zero.

6. The pop() method’s optional argument i defaults to -1, so that by default the last item is removed and returned.

7. The sort() and reverse() methods modify the list in place for economy of space when sorting or reversing a large list. To remind you that they operate by side effect, they don’t return the sorted or reversed list.

8. The sort() method takes optional arguments for controlling the comparisons.

   cmp specifies a custom comparison function of two arguments (list items) which should return a negative, zero or positive number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument: cmp=lambda x,y: cmp(x.lower(), y.lower()). The default value is None.

   key specifies a function of one argument that is used to extract a comparison key from each list element: key=str.lower. The default value is None.

   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。

   In general, the key and reverse conversion processes are much faster than specifying an equivalent cmp function. This is because cmp is called multiple times for each list element while key and reverse touch each element only once. Use functools.cmp_to_key() to convert an old-style cmp function to a key function.

   在 2.3 版更改: Support for None as an equivalent to omitting cmp was added.

   在 2.4 版更改: Support for key and reverse was added.

9. Starting with Python 2.3, 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).

10. 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 2.3 and newer makes the list appear empty for the duration, and raises ValueError if it can detect that the list has been mutated during a sort.

11. 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 Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange.

5.7. 集合类型 — 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.)

2.4 新版功能.

与其他多项集一样，集合也支持 x in set, len(set) 和 for x in set。 作为一种无序的多项集，集合并不记录元素位置或插入顺序。 相应地，集合不支持索引、切片或其他序列类的操作。

目前有两种内置集合类型，set 和 frozenset。 set 类型是可变的 — 其内容可以使用 add() 和 remove() 这样的方法来改变。 由于是可变类型，它没有哈希值，且不能被用作字典的键或其他集合的元素。 frozenset 类型是不可变并且为 hashable — 其内容在被创建后不能再改变；因此它可以被用作字典的键或其他集合的元素。

As of Python 2.7, 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.

两个类的构造器具有相同的作用方式：

class set([iterable])

class frozenset([iterable])

返回一个新的 set 或 frozenset 对象，其元素来自于 iterable。 集合的元素必须为 hashable。 要表示由集合对象构成的集合，所有的内层集合必须为 frozenset 对象。 如果未指定 iterable，则将返回一个新的空集合。

set 和 frozenset 的实例提供以下操作：

len(s)

返回集合 s 中的元素数量（即 s 的基数）。

x in s

检测 x 是否为 s 中的成员。

x not in s

检测 x 是否非 s 中的成员。

isdisjoint(other)

如果集合中没有与 other 共有的元素则返回 True。 当且仅当两个集合的交集为空集合时，两者为不相交集合。

2.6 新版功能.

issubset(other)

set <= other

检测是否集合中的每个元素都在 other 之中。

set < other

检测集合是否为 other 的真子集，即 set <= other and set != other。

issuperset(other)

set >= other

检测是否 other 中的每个元素都在集合之中。

set > other

检测集合是否为 other 的真超集，即 set >= other and set != other。

union(*others)

set | other | ...

返回一个新集合，其中包含来自原集合以及 others 指定的所有集合中的元素。

在 2.6 版更改: Accepts multiple input iterables.

intersection(*others)

set & other & ...

返回一个新集合，其中包含原集合以及 others 指定的所有集合中共有的元素。

在 2.6 版更改: Accepts multiple input iterables.

difference(*others)

set - other - ...

返回一个新集合，其中包含原集合中在 others 指定的其他集合中不存在的元素。

在 2.6 版更改: Accepts multiple input iterables.

symmetric_difference(other)

set ^ other

返回一个新集合，其中的元素或属于原集合或属于 other 指定的其他集合，但不能同时属于两者。

copy()

返回原集合的浅拷贝。

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 non-empty 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. Accordingly, sets do not implement the __cmp__() method.

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.

在 2.6 版更改: Accepts multiple input iterables.

intersection_update(*others)

set &= other & ...

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

在 2.6 版更改: Accepts multiple input iterables.

difference_update(*others)

set -= other | ...

Update the set, removing elements found in others.

在 2.6 版更改: Accepts multiple input iterables.

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.

参见

Comparison to the built-in set types

Differences between the sets module and the built-in set types.

5.8. 映射类型 — 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.

2.2 新版功能.

在 2.3 版更改: Support for building a dictionary from keyword arguments added.

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.

2.5 新版功能: Recognition of __missing__ methods of dict subclasses.

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.

2.2 新版功能.

key not in d

Equivalent to not key in d.

2.2 新版功能.

iter(d)

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

clear()

Remove all items from the dictionary.

copy()

Return a shallow copy of the dictionary.

fromkeys(seq[, value])

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

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

2.3 新版功能.

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.

has_key(key)

Test for the presence of key in the dictionary. has_key() is deprecated in favor of key in d.

items()

Return a copy of the dictionary’s list of (key, value) pairs.

CPython implementation detail: Keys and values are listed in an arbitrary order which is non-random, varies across Python implementations, and depends on the dictionary’s history of insertions and deletions.

If items(), keys(), values(), iteritems(), iterkeys(), and itervalues() are called with no intervening modifications to the dictionary, the lists will directly correspond. This allows the creation of (value, key) pairs using zip(): pairs = zip(d.values(), d.keys()). The same relationship holds for the iterkeys() and itervalues() methods: pairs = zip(d.itervalues(), d.iterkeys()) provides the same value for pairs. Another way to create the same list is pairs = [(v, k) for (k, v) in d.iteritems()].

iteritems()

Return an iterator over the dictionary’s (key, value) pairs. See the note for dict.items().

Using iteritems() while adding or deleting entries in the dictionary may raise a RuntimeError or fail to iterate over all entries.

2.2 新版功能.

iterkeys()

Return an iterator over the dictionary’s keys. See the note for dict.items().

Using iterkeys() while adding or deleting entries in the dictionary may raise a RuntimeError or fail to iterate over all entries.

2.2 新版功能.

itervalues()

Return an iterator over the dictionary’s values. See the note for dict.items().

Using itervalues() while adding or deleting entries in the dictionary may raise a RuntimeError or fail to iterate over all entries.

2.2 新版功能.

keys()

Return a copy of the dictionary’s list of keys. See the note for dict.items().

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.

2.3 新版功能.

popitem()

Remove and return an arbitrary (key, value) pair from the dictionary.

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.

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 default 。 default 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).

在 2.4 版更改: Allowed the argument to be an iterable of key/value pairs and allowed keyword arguments.

values()

Return a copy of the dictionary’s list of values. See the note for dict.items().

viewitems()

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

2.7 新版功能.

viewkeys()

Return a new view of the dictionary’s keys. See below for documentation of view objects.

2.7 新版功能.

viewvalues()

Return a new view of the dictionary’s values. See below for documentation of view objects.

2.7 新版功能.

Dictionaries compare equal if and only if they have the same (key, value) pairs.

5.8.1. Dictionary view objects

The objects returned by dict.viewkeys(), dict.viewvalues() and dict.viewitems() 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 an arbitrary order which is non-random, varies across Python implementations, and depends on the dictionary’s history of insertions and deletions. If keys, values and items views are iterated over with no intervening modifications to the dictionary, the order of items will directly correspond. 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.

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).

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.) Then these set operations are available (“other” refers either to another view or a set):

dictview & other

Return the intersection of the dictview and the other object as a new set.

dictview | other

Return the union of the dictview and the other object as a new set.

dictview - other

Return the difference between the dictview and the other object (all elements in dictview that aren’t in other) as a new set.

dictview ^ other

Return the symmetric difference (all elements either in dictview or other, but not in both) of the dictview and the other object as a new set.

An example of dictionary view usage:

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

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

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

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

>>> # set operations
>>> keys & {'eggs', 'bacon', 'salad'}
{'bacon'}

5.9. File Objects

File objects are implemented using C’s stdio package and can be created with the built-in open() function. File objects are also returned by some other built-in functions and methods, such as os.popen() and os.fdopen() and the makefile() method of socket objects. Temporary files can be created using the tempfile module, and high-level file operations such as copying, moving, and deleting files and directories can be achieved with the shutil module.

When a file operation fails for an I/O-related reason, the exception IOError is raised. This includes situations where the operation is not defined for some reason, like seek() on a tty device or writing a file opened for reading.

Files have the following methods:

file.close()

Close the file. A closed file cannot be read or written any more. Any operation which requires that the file be open will raise a ValueError after the file has been closed. Calling close() more than once is allowed.

As of Python 2.5, you can avoid having to call this method explicitly if you use the with statement. For example, the following code will automatically close f when the with block is exited:

from __future__ import with_statement # This isn't required in Python 2.6

with open("hello.txt") as f:
    for line in f:
        print line,

In older versions of Python, you would have needed to do this to get the same effect:

f = open("hello.txt")
try:
    for line in f:
        print line,
finally:
    f.close()

注解

Not all “file-like” types in Python support use as a context manager for the with statement. If your code is intended to work with any file-like object, you can use the function contextlib.closing() instead of using the object directly.

file.flush()

Flush the internal buffer, like stdio’s fflush(). This may be a no-op on some file-like objects.

注解

flush() does not necessarily write the file’s data to disk. Use flush() followed by os.fsync() to ensure this behavior.

file.fileno()

Return the integer “file descriptor” that is used by the underlying implementation to request I/O operations from the operating system. This can be useful for other, lower level interfaces that use file descriptors, such as the fcntl module or os.read() and friends.

注解

File-like objects which do not have a real file descriptor should not provide this method!

file.isatty()

Return True if the file is connected to a tty(-like) device, else False.

注解

If a file-like object is not associated with a real file, this method should not be implemented.

file.next()

A file object is its own iterator, for example iter(f) returns f (unless f is closed). When a file is used as an iterator, typically in a for loop (for example, for line in f: print line.strip()), the next() method is called repeatedly. This method returns the next input line, or raises StopIteration when EOF is hit when the file is open for reading (behavior is undefined when the file is open for writing). In order to make a for loop the most efficient way of looping over the lines of a file (a very common operation), the next() method uses a hidden read-ahead buffer. As a consequence of using a read-ahead buffer, combining next() with other file methods (like readline()) does not work right. However, using seek() to reposition the file to an absolute position will flush the read-ahead buffer.

2.3 新版功能.

file.read([size])

Read at most size bytes from the file (less if the read hits EOF before obtaining size bytes). If the size argument is negative or omitted, read all data until EOF is reached. The bytes are returned as a string object. An empty string is returned when EOF is encountered immediately. (For certain files, like ttys, it makes sense to continue reading after an EOF is hit.) Note that this method may call the underlying C function fread() more than once in an effort to acquire as close to size bytes as possible. Also note that when in non-blocking mode, less data than was requested may be returned, even if no size parameter was given.

注解

This function is simply a wrapper for the underlying fread() C function, and will behave the same in corner cases, such as whether the EOF value is cached.

file.readline([size])

Read one entire line from the file. A trailing newline character is kept in the string (but may be absent when a file ends with an incomplete line). [6] If the size argument is present and non-negative, it is a maximum byte count (including the trailing newline) and an incomplete line may be returned. When size is not 0, an empty string is returned only when EOF is encountered immediately.

注解

Unlike stdio’s fgets(), the returned string contains null characters ('\0') if they occurred in the input.

file.readlines([sizehint])

Read until EOF using readline() and return a list containing the lines thus read. If the optional sizehint argument is present, instead of reading up to EOF, whole lines totalling approximately sizehint bytes (possibly after rounding up to an internal buffer size) are read. Objects implementing a file-like interface may choose to ignore sizehint if it cannot be implemented, or cannot be implemented efficiently.

file.xreadlines()

This method returns the same thing as iter(f).

2.1 新版功能.

2.3 版后已移除: Use for line in file instead.

file.seek(offset[, whence])

Set the file’s current position, like stdio’s fseek(). The whence argument is optional and defaults to os.SEEK_SET or 0 (absolute file positioning); other values are os.SEEK_CUR or 1 (seek relative to the current position) and os.SEEK_END or 2 (seek relative to the file’s end). There is no return value.

For example, f.seek(2, os.SEEK_CUR) advances the position by two and f.seek(-3, os.SEEK_END) sets the position to the third to last.

Note that if the file is opened for appending (mode 'a' or 'a+'), any seek() operations will be undone at the next write. If the file is only opened for writing in append mode (mode 'a'), this method is essentially a no-op, but it remains useful for files opened in append mode with reading enabled (mode 'a+'). If the file is opened in text mode (without 'b'), only offsets returned by tell() are legal. Use of other offsets causes undefined behavior.

Note that not all file objects are seekable.

在 2.6 版更改: Passing float values as offset has been deprecated.

file.tell()

Return the file’s current position, like stdio’s ftell().

注解

On Windows, tell() can return illegal values (after an fgets()) when reading files with Unix-style line-endings. Use binary mode ('rb') to circumvent this problem.

file.truncate([size])

Truncate the file’s size. If the optional size argument is present, the file is truncated to (at most) that size. The size defaults to the current position. The current file position is not changed. Note that if a specified size exceeds the file’s current size, the result is platform-dependent: possibilities include that the file may remain unchanged, increase to the specified size as if zero-filled, or increase to the specified size with undefined new content. Availability: Windows, many Unix variants.

file.write(str)

Write a string to the file. There is no return value. Due to buffering, the string may not actually show up in the file until the flush() or close() method is called.

file.writelines(sequence)

Write a sequence of strings to the file. The sequence can be any iterable object producing strings, typically a list of strings. There is no return value. (The name is intended to match readlines(); writelines() does not add line separators.)

Files support the iterator protocol. Each iteration returns the same result as readline(), and iteration ends when the readline() method returns an empty string.

File objects also offer a number of other interesting attributes. These are not required for file-like objects, but should be implemented if they make sense for the particular object.

file.closed

bool indicating the current state of the file object. This is a read-only attribute; the close() method changes the value. It may not be available on all file-like objects.

file.encoding

The encoding that this file uses. When Unicode strings are written to a file, they will be converted to byte strings using this encoding. In addition, when the file is connected to a terminal, the attribute gives the encoding that the terminal is likely to use (that information might be incorrect if the user has misconfigured the terminal). The attribute is read-only and may not be present on all file-like objects. It may also be None, in which case the file uses the system default encoding for converting Unicode strings.

2.3 新版功能.

file.errors

The Unicode error handler used along with the encoding.

2.6 新版功能.

file.mode

The I/O mode for the file. If the file was created using the open() built-in function, this will be the value of the mode parameter. This is a read-only attribute and may not be present on all file-like objects.

file.name

If the file object was created using open(), the name of the file. Otherwise, some string that indicates the source of the file object, of the form <...>. This is a read-only attribute and may not be present on all file-like objects.

file.newlines

If Python was built with universal newlines enabled (the default) this read-only attribute exists, and for files opened in universal newline read mode it keeps track of the types of newlines encountered while reading the file. The values it can take are '\r', '\n', '\r\n', None (unknown, no newlines read yet) or a tuple containing all the newline types seen, to indicate that multiple newline conventions were encountered. For files not opened in universal newlines read mode the value of this attribute will be None.

file.softspace

Boolean that indicates whether a space character needs to be printed before another value when using the print statement. Classes that are trying to simulate a file object should also have a writable softspace attribute, which should be initialized to zero. This will be automatic for most classes implemented in Python (care may be needed for objects that override attribute access); types implemented in C will have to provide a writable softspace attribute.

注解

This attribute is not used to control the print statement, but to allow the implementation of print to keep track of its internal state.

5.10. memoryview type

2.7 新版功能.

memoryview objects allow Python code to access the internal data of an object that supports the buffer protocol without copying. Memory is generally interpreted as simple bytes.

class memoryview(obj)

Create a memoryview that references obj. obj must support the buffer protocol. Built-in objects that support the buffer protocol include str and bytearray (but not unicode).

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 str and bytearray, an element is a single byte, but other third-party types may expose larger elements.

len(view) returns the total number of elements in the memoryview, view. The itemsize attribute will give you the number of bytes in a single element.

A memoryview supports slicing to expose its data. Taking a single index will return a single element as a str object. Full slicing will result in a subview:

>>> v = memoryview('abcefg')
>>> v[1]
'b'
>>> v[-1]
'g'
>>> v[1:4]
<memory at 0x77ab28>
>>> v[1:4].tobytes()
'bce'

If the object the memoryview is over supports changing its data, the memoryview supports slice assignment:

>>> data = bytearray('abcefg')
>>> v = memoryview(data)
>>> v.readonly
False
>>> v[0] = 'z'
>>> data
bytearray(b'zbcefg')
>>> v[1:4] = '123'
>>> data
bytearray(b'z123fg')
>>> v[2] = 'spam'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: cannot modify size of memoryview object

Notice how the size of the memoryview object cannot be changed.

memoryview has two methods:

tobytes()

Return the data in the buffer as a bytestring (an object of class str).

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

tolist()

Return the data in the buffer as a list of integers.

>>> memoryview("abc").tolist()
[97, 98, 99]

还存在一些可用的只读属性：

format

A string containing the format (in struct module style) for each element in the view. This defaults to 'B', a simple bytestring.

itemsize

The size in bytes of each element of the memoryview.

shape

一个整数元组，通过 ndim 的长度值给出内存所代表的 N 维数组的形状。

ndim

一个整数，表示内存所代表的多维数组具有多少个维度。

strides

一个整数元组，通过 ndim 的长度给出以字节表示的大小，以便访问数组中每个维度上的每个元素。

readonly

一个表明内存是否只读的布尔值。

5.11. Context Manager Types

2.5 新版功能.

Python’s with statement supports the concept of a runtime context defined by a context manager. This is implemented using two separate 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.

The context management protocol consists of a pair of methods that need to be provided for a context manager object to define a runtime context:

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 (such as contextlib.nested) 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.

5.12. Other Built-in Types

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

5.12.1. 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'>.

5.12.2. Classes and Class Instances

See 对象、值与类型 and 类定义 for these.

5.12.3. 函数

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.

5.12.4. 方法

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.

The implementation adds two special read-only attributes to class instance methods: m.im_self is the object on which the method operates, and m.im_func is the function implementing the method. Calling m(arg-1, arg-2, ..., arg-n) is completely equivalent to calling m.im_func(m.im_self, arg-1, arg-2, ..., arg-n).

Class instance methods are either bound or unbound, referring to whether the method was accessed through an instance or a class, respectively. When a method is unbound, its im_self attribute will be None and if called, an explicit self object must be passed as the first argument. In this case, self must be an instance of the unbound method’s class (or a subclass of that class), otherwise a TypeError is raised.

Like function objects, methods objects support getting arbitrary attributes. However, since method attributes are actually stored on the underlying function object (meth.im_func), setting method attributes on either bound or unbound 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: 'instancemethod' object has no attribute 'whoami'
>>> c.method.im_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.

5.12.5. 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 func_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 statement or the built-in eval() function.

See 标准类型层级结构 for more information.

5.12.6. Type 对象

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: <type 'int'>.

5.12.7. 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).

It is written as None.

5.12.8. The Ellipsis Object

This object is used by extended slice notation (see 切片). It supports no special operations. There is exactly one ellipsis object, named Ellipsis (a built-in name).

It is written as Ellipsis. When in a subscript, it can also be written as ..., for example seq[...].

5.12.9. 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.

It is written as NotImplemented.

5.12.10. 布尔值

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.

5.12.11. Internal Objects

See 标准类型层级结构 for this information. It describes stack frame objects, traceback objects, and slice objects.

5.13. 特殊属性

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.

object.__methods__

2.2 版后已移除: Use the built-in function dir() to get a list of an object’s attributes. This attribute is no longer available.

object.__members__

2.2 版后已移除: Use the built-in function dir() to get a list of an object’s attributes. This attribute is no longer available.

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, type, function, method, descriptor, or generator instance.

The following attributes are only supported by new-style classes.

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 new-style 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__()
[<type '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]	To format only a tuple you should therefore provide a singleton tuple whose only element is the tuple to be formatted.

[6]

The advantage of leaving the newline on is that returning an empty string is then an unambiguous EOF indication. It is also possible (in cases where it might matter, for example, if you want to make an exact copy of a file while scanning its lines) to tell whether the last line of a file ended in a newline or not (yes this happens!).