4. 其他流程控制工具

除了刚刚介绍过的 while 语句,Python 中也会使用其他语言中常见的流程控制语句,只是稍有变化。

4.1. if Statements

可能最为人所熟知的编程语句就是 if 语句了。例如

>>> x = int(raw_input("Please enter an integer: "))
Please enter an integer: 42
>>> if x < 0:
...     x = 0
...     print 'Negative changed to zero'
... elif x == 0:
...     print 'Zero'
... elif x == 1:
...     print 'Single'
... else:
...     print 'More'

There can be zero or more elif parts, and the else part is optional. The keyword ‘elif’ is short for ‘else if’, and is useful to avoid excessive indentation. An ifelifelif … sequence is a substitute for the switch or case statements found in other languages.

4.2. for Statements

The for statement in Python differs a bit from what you may be used to in C or Pascal. Rather than always iterating over an arithmetic progression of numbers (like in Pascal), or giving the user the ability to define both the iteration step and halting condition (as C), Python’s for statement iterates over the items of any sequence (a list or a string), in the order that they appear in the sequence. For example (no pun intended):

>>> # Measure some strings:
... words = ['cat', 'window', 'defenestrate']
>>> for w in words:
...     print w, len(w)
cat 3
window 6
defenestrate 12


>>> for w in words[:]:  # Loop over a slice copy of the entire list.
...     if len(w) > 6:
...         words.insert(0, w)
>>> words
['defenestrate', 'cat', 'window', 'defenestrate']

4.3. range() 函数

If you do need to iterate over a sequence of numbers, the built-in function range() comes in handy. It generates lists containing arithmetic progressions:

>>> range(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

The given end point is never part of the generated list; range(10) generates a list of 10 values, the legal indices for items of a sequence of length 10. It is possible to let the range start at another number, or to specify a different increment (even negative; sometimes this is called the ‘step’):

>>> range(5, 10)
[5, 6, 7, 8, 9]
>>> range(0, 10, 3)
[0, 3, 6, 9]
>>> range(-10, -100, -30)
[-10, -40, -70]

要以序列的索引来迭代,您可以将 range()len() 组合如下:

>>> a = ['Mary', 'had', 'a', 'little', 'lamb']
>>> for i in range(len(a)):
...     print i, a[i]
0 Mary
1 had
2 a
3 little
4 lamb

然而,在大多数这类情况下,使用 enumerate() 函数比较方便,请参见 循环的技巧

4.4. break and continue Statements, and else Clauses on Loops

break 语句,和 C 中的类似,用于跳出最近的 forwhile 循环.

Loop statements may have an else clause; it is executed when the loop terminates through exhaustion of the list (with for) or when the condition becomes false (with while), but not when the loop is terminated by a break statement. This is exemplified by the following loop, which searches for prime numbers:

>>> for n in range(2, 10):
...     for x in range(2, n):
...         if n % x == 0:
...             print n, 'equals', x, '*', n/x
...             break
...     else:
...         # loop fell through without finding a factor
...         print n, 'is a prime number'
2 is a prime number
3 is a prime number
4 equals 2 * 2
5 is a prime number
6 equals 2 * 3
7 is a prime number
8 equals 2 * 4
9 equals 3 * 3

(是的,这是正确的代码。仔细看: else 子句属于 for 循环, 不属于 if 语句。)

When used with a loop, the else clause has more in common with the else clause of a try statement than it does that of if statements: a try statement’s else clause runs when no exception occurs, and a loop’s else clause runs when no break occurs. For more on the try statement and exceptions, see 处理异常.

continue 语句也是借鉴自 C 语言,表示继续循环中的下一次迭代:

>>> for num in range(2, 10):
...     if num % 2 == 0:
...         print "Found an even number", num
...         continue
...     print "Found a number", num
Found an even number 2
Found a number 3
Found an even number 4
Found a number 5
Found an even number 6
Found a number 7
Found an even number 8
Found a number 9

4.5. pass Statements

pass 语句什么也不做。当语法上需要一个语句,但程序需要什么动作也不做时,可以使用它。例如:

>>> while True:
...     pass  # Busy-wait for keyboard interrupt (Ctrl+C)


>>> class MyEmptyClass:
...     pass

Another place pass can be used is as a place-holder for a function or conditional body when you are working on new code, allowing you to keep thinking at a more abstract level. The pass is silently ignored:

>>> def initlog(*args):
...     pass   # Remember to implement this!

4.6. 定义函数

我们可以创建一个输出任意范围内 Fibonacci 数列的函数:

>>> def fib(n):    # write Fibonacci series up to n
...     """Print a Fibonacci series up to n."""
...     a, b = 0, 1
...     while a < n:
...         print a,
...         a, b = b, a+b
>>> # Now call the function we just defined:
... fib(2000)
0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597

关键字 def 引入一个函数 定义。它必须后跟函数名称和带括号的形式参数列表。构成函数体的语句从下一行开始,并且必须缩进。

函数体的第一个语句可以(可选的)是字符串文字;这个字符串文字是函数的文档字符串或 docstring 。(有关文档字符串的更多信息,请参阅 文档字符串 部分)有些工具使用文档字符串自动生成在线或印刷文档,或者让用户以交互式的形式浏览代码;在你编写的代码中包含文档字符串是一种很好的做法,所以要养成习惯。

The execution of a function introduces a new symbol table used for the local variables of the function. More precisely, all variable assignments in a function store the value in the local symbol table; whereas variable references first look in the local symbol table, then in the local symbol tables of enclosing functions, then in the global symbol table, and finally in the table of built-in names. Thus, global variables cannot be directly assigned a value within a function (unless named in a global statement), although they may be referenced.

在函数被调用时,实际参数(实参)会被引入被调用函数的本地符号表中;因此,实参是通过 按值调用 传递的(其中 始终是对象 引用 而不是对象的值)。1 当一个函数调用另外一个函数时,将会为该调用创建一个新的本地符号表。


>>> fib
<function fib at 10042ed0>
>>> f = fib
>>> f(100)
0 1 1 2 3 5 8 13 21 34 55 89

Coming from other languages, you might object that fib is not a function but a procedure since it doesn’t return a value. In fact, even functions without a return statement do return a value, albeit a rather boring one. This value is called None (it’s a built-in name). Writing the value None is normally suppressed by the interpreter if it would be the only value written. You can see it if you really want to using print:

>>> fib(0)
>>> print fib(0)


>>> def fib2(n):  # return Fibonacci series up to n
...     """Return a list containing the Fibonacci series up to n."""
...     result = []
...     a, b = 0, 1
...     while a < n:
...         result.append(a)    # see below
...         a, b = b, a+b
...     return result
>>> f100 = fib2(100)    # call it
>>> f100                # write the result
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]

此示例中,像往常一样,演示了一些新的 Python 功能:

  • The return statement returns with a value from a function. return without an expression argument returns None. Falling off the end of a function also returns None.

  • result.append(a) 语句调用了列表对象 result方法 。方法是“属于”一个对象的函数,它被命名为 obj.methodname ,其中 obj 是某个对象(也可能是一个表达式), methodname 是由对象类型中定义的方法的名称。不同的类型可以定义不同的方法。不同类型的方法可以有相同的名称而不会引起歧义。(可以使用 定义自己的对象类型和方法,请参阅 )示例中的方法 append() 是为列表对象定义的;它会在列表的最后添加一个新的元素。在这个示例中它相当于 result = result + [a] ,但更高效。

4.7. 函数定义的更多形式


4.7.1. 参数默认值


def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):
    while True:
        ok = raw_input(prompt)
        if ok in ('y', 'ye', 'yes'):
            return True
        if ok in ('n', 'no', 'nop', 'nope'):
            return False
        retries = retries - 1
        if retries < 0:
            raise IOError('refusenik user')
        print complaint


  • 只给出必需的参数:ask_ok('Do you really want to quit?')

  • 给出一个可选的参数:ask_ok('OK to overwrite the file?', 2)

  • 或者给出所有的参数:ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!')

这个示例还介绍了 in 关键字。它可以测试一个序列是否包含某个值。

默认值是在 定义过程 中在函数定义处计算的,所以

i = 5

def f(arg=i):
    print arg

i = 6

会打印 5

重要警告: 默认值只会执行一次。这条规则在默认值为可变对象(列表、字典以及大多数类实例)时很重要。比如,下面的函数会存储在后续调用中传递给它的参数:

def f(a, L=[]):
    return L

print f(1)
print f(2)
print f(3)


[1, 2]
[1, 2, 3]


def f(a, L=None):
    if L is None:
        L = []
    return L

4.7.2. 关键字参数

也可以使用形如 kwarg=value关键字参数 来调用函数。例如下面的函数:

def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
    print "-- This parrot wouldn't", action,
    print "if you put", voltage, "volts through it."
    print "-- Lovely plumage, the", type
    print "-- It's", state, "!"

接受一个必需的参数(voltage)和三个可选的参数(state, action,和 type)。这个函数可以通过下面的任何一种方式调用:

parrot(1000)                                          # 1 positional argument
parrot(voltage=1000)                                  # 1 keyword argument
parrot(voltage=1000000, action='VOOOOOM')             # 2 keyword arguments
parrot(action='VOOOOOM', voltage=1000000)             # 2 keyword arguments
parrot('a million', 'bereft of life', 'jump')         # 3 positional arguments
parrot('a thousand', state='pushing up the daisies')  # 1 positional, 1 keyword


parrot()                     # required argument missing
parrot(voltage=5.0, 'dead')  # non-keyword argument after a keyword argument
parrot(110, voltage=220)     # duplicate value for the same argument
parrot(actor='John Cleese')  # unknown keyword argument

在函数调用中,关键字参数必须跟随在位置参数的后面。传递的所有关键字参数必须与函数接受的其中一个参数匹配(比如 actor 不是函数 parrot 的有效参数),它们的顺序并不重要。这也包括非可选参数,(比如 parrot(voltage=1000) 也是有效的)。不能对同一个参数多次赋值。下面是一个因为此限制而失败的例子:

>>> def function(a):
...     pass
>>> function(0, a=0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: function() got multiple values for keyword argument 'a'

When a final formal parameter of the form **name is present, it receives a dictionary (see 映射类型 — dict) containing all keyword arguments except for those corresponding to a formal parameter. This may be combined with a formal parameter of the form *name (described in the next subsection) which receives a tuple containing the positional arguments beyond the formal parameter list. (*name must occur before **name.) For example, if we define a function like this:

def cheeseshop(kind, *arguments, **keywords):
    print "-- Do you have any", kind, "?"
    print "-- I'm sorry, we're all out of", kind
    for arg in arguments:
        print arg
    print "-" * 40
    keys = sorted(keywords.keys())
    for kw in keys:
        print kw, ":", keywords[kw]


cheeseshop("Limburger", "It's very runny, sir.",
           "It's really very, VERY runny, sir.",
           shopkeeper='Michael Palin',
           client="John Cleese",
           sketch="Cheese Shop Sketch")


-- Do you have any Limburger ?
-- I'm sorry, we're all out of Limburger
It's very runny, sir.
It's really very, VERY runny, sir.
client : John Cleese
shopkeeper : Michael Palin
sketch : Cheese Shop Sketch

Note that the list of keyword argument names is created by sorting the result of the keywords dictionary’s keys() method before printing its contents; if this is not done, the order in which the arguments are printed is undefined.

4.7.3. 任意的参数列表

最后,最不常用的选项是可以使用任意数量的参数调用函数。这些参数会被包含在一个元组里(参见 元组和序列 )。在可变数量的参数之前,可能会出现零个或多个普通参数。:

def write_multiple_items(file, separator, *args):

4.7.4. 解包参数列表

The reverse situation occurs when the arguments are already in a list or tuple but need to be unpacked for a function call requiring separate positional arguments. For instance, the built-in range() function expects separate start and stop arguments. If they are not available separately, write the function call with the *-operator to unpack the arguments out of a list or tuple:

>>> range(3, 6)             # normal call with separate arguments
[3, 4, 5]
>>> args = [3, 6]
>>> range(*args)            # call with arguments unpacked from a list
[3, 4, 5]

In the same fashion, dictionaries can deliver keyword arguments with the **-operator:

>>> def parrot(voltage, state='a stiff', action='voom'):
...     print "-- This parrot wouldn't", action,
...     print "if you put", voltage, "volts through it.",
...     print "E's", state, "!"
>>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"}
>>> parrot(**d)
-- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !

4.7.5. Lambda 表达式

可以用 lambda 关键字来创建一个小的匿名函数。这个函数返回两个参数的和: lambda a, b: a+b 。Lambda函数可以在需要函数对象的任何地方使用。它们在语法上限于单个表达式。从语义上来说,它们只是正常函数定义的语法糖。与嵌套函数定义一样,lambda函数可以引用所包含域的变量:

>>> def make_incrementor(n):
...     return lambda x: x + n
>>> f = make_incrementor(42)
>>> f(0)
>>> f(1)


>>> pairs = [(1, 'one'), (2, 'two'), (3, 'three'), (4, 'four')]
>>> pairs.sort(key=lambda pair: pair[1])
>>> pairs
[(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')]

4.7.6. 文档字符串

There are emerging conventions about the content and formatting of documentation strings.



Python 解析器不会从 Python 中删除多行字符串文字的缩进,因此处理文档的工具必须在需要时删除缩进。 这是使用以下约定完成的。 文档字符串第一行 之后 的第一个非空行确定整个文档字符串的缩进量。(我们不能使用第一行,因为它通常与字符串的开头引号相邻,因此它的缩进在字符串文字中不明显。)然后从字符串的所有行的开头剥离与该缩进 “等效” 的空格。 缩进更少的行不应该出现,但是如果它们出现,则应该剥离它们的所有前导空格。 应在转化制表符为空格后测试空格的等效性(通常转化为8个空格)。


>>> def my_function():
...     """Do nothing, but document it.
...     No, really, it doesn't do anything.
...     """
...     pass
>>> print my_function.__doc__
Do nothing, but document it.

    No, really, it doesn't do anything.

4.8. 小插曲:编码风格

现在你将要写更长,更复杂的 Python 代码,是时候讨论一下 代码风格 了。 大多数语言都能以不同的风格被编写(或更准确地说,被格式化);有些比其他的更具有可读性。 能让其他人轻松阅读你的代码总是一个好主意,采用一种好的编码风格对此有很大帮助。

对于Python,PEP 8 已经成为大多数项目所遵循的风格指南;它促进了一种非常易读且令人赏心悦目的编码风格。每个Python开发人员都应该在某个时候阅读它;以下是为你提取的最重要的几个要点:

  • 使用4个空格缩进,不要使用制表符。


  • 换行,使一行不超过79个字符。


  • 使用空行分隔函数和类,以及函数内的较大的代码块。

  • 如果可能,把注释放到单独的一行。

  • 使用文档字符串。

  • 在运算符前后和逗号后使用空格,但不能直接在括号内使用: a = f(1, 2) + g(3, 4)

  • Name your classes and functions consistently; the convention is to use CamelCase for classes and lower_case_with_underscores for functions and methods. Always use self as the name for the first method argument (see 初探类 for more on classes and methods).

  • Don’t use fancy encodings if your code is meant to be used in international environments. Plain ASCII works best in any case.



实际上,通过对象引用调用 会是一个更好的表述,因为如果传递的是可变对象,则调用者将看到被调用者对其做出的任何更改(插入到列表中的元素)。