Python 官方简明教程 4

-4. 更多的控制流工具（已翻译完毕，尚未校对）

感谢remeber翻译本页（尚未校对），欢迎大家到Python开发者网络PYDN参加 Pythn 3.2 文档的翻译工作

除了介绍过的while语句,Python熟悉其它语言中已知的常用控制流语句. Besides the while statement just introduced, Python knows the usual control flow statements known from other languages, with some twists.

-4.1. if语句 if Statements

if语句也许是最知名的语句类型.例如: Perhaps the most well-known statement type is the if statement. For example:

>>> x = int(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')
...
More

这里可以没有或有更多的elif部分,而else部分则是可选的.关键字'elif'是'else if'的缩写,可以有效的避免过度的缩进.一套 if...elif...elif...序列可以作为其它语言中的swith或case语句的替代. 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 if ... elif ... elif ... sequence is a substitute for the switch or case statements found in other languages.

-4.2. for语句 for Statements

Python中的for语句和您在C或Pascal语言中的用法略有不同.它既不会遍历数列中的数字(如Pascal中一样),也不会让用户定义迭代步长和中止条件(如C),Python的for循环会以各项在序列中出现的顺序遍历序列(如列表或字符串)的所有项,例如(此处非双关语): 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:
... a = ['cat', 'window', 'defenestrate']
>>> for x in a:
...     print(x, len(x))
...
cat 3
window 6
defenestrate 12

在循环中遍历序列时对其修改是不安全的(这只发生在可变序列类型中，如列表).如果您需要在遍历时(例如,复制选定选项)修改列表,您必须遍历一个拷贝.分片表达式会使这变得非常方便: It is not safe to modify the sequence being iterated over in the loop (this can only happen for mutable sequence types, such as lists). If you need to modify the list you are iterating over (for example, to duplicate selected items) you must iterate over a copy. The slice notation makes this particularly convenient:

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

-4.3. range()函数 The range() Function

如果您需要遍历数字序列，内置函数range正派上用场.它会生成数列,例如: If you do need to iterate over a sequence of numbers, the built-in function range() comes in handy. It generates arithmetic progressions:

>>> for i in range(5):
...     print(i)
...
0
1
2
3
4

给定的终点并不在产生的序列之内;range(10)会产生10个数值，对这个长度为10的序列中所有项进行索引是合适的.也可以使range以其它数字开始或指定不同的增量(甚至可以是负数;有时这也叫做'步长'): The given end point is never part of the generated sequence; range(10) generates 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 through 9

range(0, 10, 3)
   0, 3, 6, 9

range(-10, -100, -30)
  -10, -40, -70

您可以结合range()和len()函数以遍历一个序列的索引,如下所示: To iterate over the indices of a sequence, you can combine range() and len() as follows:

>>> 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

然而在大多数情况下,您可以很方便的使用enumerate()函数,以查看循环技巧. In most such cases, however, it is convenient to use the enumerate() function, see Looping Techniques.

如果您只是打印range函数,会出现奇怪的现象: A strange thing happens if you just print a range:

>>> print(range(10))
range(0, 10)

range()会以多种方式返回类似列表的对象,事实上并非真正列表.在您遍历它时,它会返回一个有着连续项的所需的序列对象,但它并不会真正地生成列表，这样做可以节省空间. In many ways the object returned by range() behaves as if it is a list, but in fact it isn’t. It is an object which returns the successive items of the desired sequence when you iterate over it, but it doesn’t really make the list, thus saving space.

我们说这个对象可迭代,意思是说适合作为函数和结构体的对象,以期在输入结束时从所获取的连续项中得到某种结果.我们已经看到for语句就是这样的迭代器.list()函数也是一个;它从可迭代量创建新列表: We say such an object is iterable, that is, suitable as a target for functions and constructs that expect something from which they can obtain successive items until the supply is exhausted. We have seen that the for statement is such an iterator. The function list() is another; it creates lists from iterables:

>>> list(range(5))
[0, 1, 2, 3, 4]

之后我们将看到更多返回可迭代量及将可迭代量作为参数的函数. Later we will see more functions that return iterables and take iterables as argument.

-4.4. break和continue语句及循环中的else子句 break and continue Statements, and else Clauses on Loops

break语句,像C语言中一样,跳出最小的封闭的for和while循环. The break statement, like in C, breaks out of the smallest enclosing for or while loop.

continue语句,同样从C语言中借鉴而来,继续循环的下一次迭代. The continue statement, also borrowed from C, continues with the next iteration of the loop.

循环语句可以有else子句;它在穷尽列表(以for循环)或条件变为假(以while循环)循环终止时被执行,但循环被break终止时不执行.如下查寻质数的循环例子: 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

-4.5. pass语句 pass Statements

pass语句什么都不做.它只在语法上需要一条语句但程序不需要任何操作时使用.例如: The pass statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example:

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

这通常用作创建最小的类: This is commonly used for creating minimal classes:

>>> class MyEmptyClass:
...     pass
...

pass可以在您编写新代码时作为函数或条件体的占位符，方便您以更抽象的层次考虑.pass默认将被忽略掉: 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 Defining Functions

我们可以创建一个函数来写出一定范围内的斐波纳契数列: We can create a function that writes the Fibonacci series to an arbitrary boundary:

>>> 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, end=' ')
...         a, b = b, a+b
...     print()
...
>>> # 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作为函数定义的开头.之后必须跟着函数名和小括号包括的形参列表.从下一行的开始的表达式构成函数体,其中的所有行都必须缩进. The keyword def introduces a function definition. It must be followed by the function name and the parenthesized list of formal parameters. The statements that form the body of the function start at the next line, and must be indented.

函数体的第一条语句可选为字符串;这个字符串是函数的文档字符亦或doctring.(更多关于docstrings的内容参考文档字符串部分.)Python提供了一些工具可以自动生成在线的或打印的文档,也可以让用户通过代码交互浏览;在您编写的代码中加入文档字符串是个很好的做法,因此请养成编写文档字符串的习惯. The first statement of the function body can optionally be a string literal; this string literal is the function’s documentation string, or docstring. (More about docstrings can be found in the section Documentation Strings.) There are tools which use docstrings to automatically produce online or printed documentation, or to let the user interactively browse through code; it’s good practice to include docstrings in code that you write, so make a habit of it.

函数执行时引入了一个专为函数本地变量提供的符号表.更准确而言,函数中所有变量赋值时都将其值储存在本地符号表中;变量引用时会先查看本地符号表，其次查看封装函数的本地符号表，再次查看全局符号表，最后查看内置函数名字表.这样,全局变量不能在一个函数内部被直接赋值(除非有global语句声明),虽然全局变量可在函数内被引用. 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.

一个函数调用实参,该实参会在被调用函数的本地符号表中引用;这样,参数通过被值调用实现传递(值总是一个对象的引用,不是对象的值).[1]当一个函数调用另一个函数时,会为此调用创建一个新的本地符号表. The actual parameters (arguments) to a function call are introduced in the local symbol table of the called function when it is called; thus, arguments are passed using call by value (where the value is always an object reference, not the value of the object). [1] When a function calls another function, a new local symbol table is created for that call.

函数定义会在当前符号表中引用函数名.该函数名的值有一个被解释器认作用户定义函数的类型.这个值可以被赋给其它函数名.这即作为一个重命名机制: A function definition introduces the function name in the current symbol table. The value of the function name has a type that is recognized by the interpreter as a user-defined function. This value can be assigned to another name which can then also be used as a function. This serves as a general renaming mechanism:

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

如果您有了解过其它语言,您可能不认为fib是个函数,因为它没有返回值,因而更像一个过程.事实上,即使没有返回语句的函数也有一个返回值,尽管是个很无趣的值.这个值即None(其为内置名).如果作为惟一的值输入,解释器通常将不予理会.您可以用print()瞧到它. 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))
None

编写函数返回以斐波那契数列的数字为元素的列表,相对于打印更加简便.(要注意return 的缩进。如果多一个Tab的缩进，将永远返回[0]) It is simple to write a function that returns a list of the numbers of the Fibonacci series, instead of printing it:

>>> 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]

这个例子一般也用来说明Python的一些新特性: This example, as usual, demonstrates some new Python features:

   * 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.
   
   * The statement result.append(a) calls a method of the list object result. A method is a function that‘belongs’
to an object and is named obj.methodname, where obj is some object (this may be an expression), and methodname is
the name of a method that is defined by the object's type. Different types define different methods. Methods of 
different types may have the same name without causing ambiguity. (It is possible to define your own object types 
and methods, using classes, see Classes) The method append() shown in the example is defined for list objects; it 
adds a new element at the end of the list. In this example it is equivalent to result = result + [a], but more 
efficient.

-4.7. 深入了解函数定义 More on Defining Functions

定义函数时也可以添加一些参数.有三种形式,可以组合使用. It is also possible to define functions with a variable number of arguments. There are three forms, which can be combined.

-4.7.1. 默认参数值 Default Argument Values

为一个或多个参数指定默认值是最有用的形式.这样会创建一个函数,其参数可少于定义的数量.例如: The most useful form is to specify a default value for one or more arguments. This creates a function that can be called with fewer arguments than it is defined to allow. For example:

def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):
    while True:
        ok = 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)

这个函数可以几种方法被调用: This function can be called in several ways:

• giving only the mandatory argument: ask_ok('Do you really want to quit?')
• giving one of the optional arguments: ask_ok('OK to overwrite the file?', 2)
• or even giving all arguments: ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!')

这个例子中引用了关键字in.它将测试一个序列是否含有某个值. This example also introduces the in keyword. This tests whether or not a sequence contains a certain value.

默认值在函数定义的范围内被赋值,所以此处将打印值5. The default values are evaluated at the point of function definition in the defining scope, so that

i = 5

def f(arg=i):
    print(arg)

i = 6
f()

will print 5.

重要警告:默认值只被赋予一次.这在默认值为列表,字典或大部分类的实例等可变对象时会产生很大影响.例如,下面的函数将在子序列调用时积累传递给它的参数: Important warning: The default value is evaluated only once. This makes a difference when the default is a mutable object such as a list, dictionary, or instances of most classes. For example, the following function accumulates the arguments passed to it on subsequent calls:

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

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

This will print

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

如果您不想和子序列调用共享默认值,您可以用以下写法替换: If you don’t want the default to be shared between subsequent calls, you can write the function like this instead:

def f(a, L=None):

   if L is None:
       L = []
   L.append(a)
   return L

-4.7.2. 关键字参数 Keyword Arguments

函数也可以使用keyword = value的关键字参数形式被调用.例如,以下函数: Functions can also be called using keyword arguments of the form keyword = value. For instance, the following function:

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

可以以下几种方式被调用: could be called in any of the following ways:

parrot(1000)
parrot(action = 'VOOOOOM', voltage = 1000000)
parrot('a thousand', state = 'pushing up the daisies')
parrot('a million', 'bereft of life', 'jump')

如下调用无效: but the following calls would all be invalid:

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

一般来说,一个参数列表必须先是位置参数,之后是关键字参数,其中的关键字必须从形式参数名中选取.形式参数是否有默认值无关紧要.没有参数能多次获取一个值-和位置参数相对应的形式参数在同一调用中不能用作关键字.这里有个因为这种限制导致错误的例子: In general, an argument list must have any positional arguments followed by any keyword arguments, where the keywords must be chosen from the formal parameter names. It’s not important whether a formal parameter has a default value or not. No argument may receive a value more than once — formal parameter names corresponding to positional arguments cannot be used as keywords in the same calls. Here’s an example that fails due to this restriction:

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

当**name形式的最终形参出现时,它将接收一个字典(查看映射类型－字典)包含除那些相对应的形式参数外的所有关键字参数.这可以和以*name形式的形参结合,该形式形参接收含有超出形参列表的位置参数的元组.(*name必须在**name前.)例如,如果我们定义一个函数如下: When a final formal parameter of the form **name is present, it receives a dictionary (see Mapping Types — 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])

它可能被这样调用: It could be called like this:

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

自然它将打印: and of course it would print:

-- 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

注意,关键字参数名列表在打印内容前被创建,并通过字典的keys()方法对关键字结果进行排序;否则参数打印顺序未定义. 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. 可变参数列表 Arbitrary Argument Lists

最后,一个最不常用的选择是可以让函数调用可变个数的参数.这些参数被包装进一个元组(查看元组和序列).在这些可变个数的参数之前,可以有零到多个普通的参数: Finally, the least frequently used option is to specify that a function can be called with an arbitrary number of arguments. These arguments will be wrapped up in a tuple (see Tuples and Sequences). Before the variable number of arguments, zero or more normal arguments may occur.

def write_multiple_items(file, separator, *args):
    file.write(separator.join(args))

通常,这些可变参数是形参列表中的最后项,因为它将接收所有剩余的传递给函数的参数.任何在*args参数之后的都是‘仅关键字’参数,意味它们只能用作关键字参数. Normally, these variadic arguments will be last in the list of formal parameters, because they scoop up all remaining input arguments that are passed to the function. Any formal parameters which occur after the *args parameter are ‘keyword-only’ arguments, meaning that they can only be used as keywords rather than positional arguments.

>>> def concat(*args, sep="/"):
...    return sep.join(args)
...
>>> concat("earth", "mars", "venus")
'earth/mars/venus'
>>> concat("earth", "mars", "venus", sep=".")
'earth.mars.venus'

-4.7.4. 拆分参数列表 Unpacking Argument Lists

另有一种相反的情况: 当你要传递的参数已经是一个列表或元组,但要调用的函数却接受分开一个个的参数值. 这时候你要把已有的列表拆开来. 例如内建函数 range() 要独立的 start, stop 参数. 你可以在调用函数时加一个 *操作符来自动把参数列表拆开: 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:

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

同样的方法,字典可以通过**操作符传递参数: 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, end=' ')
...     print("if you put", voltage, "volts through it.", end=' ')
...     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形式 Lambda Forms

出于适当的需要,有几种通常在功能性语言和 Lisp 中出现的功能加入到了 Python.通过 lambda 关键字,可以创建很小的匿名函数.这里有一个函数返回它的两个参数的和:"lambda a,b: a+b". Lambda 形式可以用于任何需要的函数对象.出于语法限制,它们只能有一个单独的表达式.语义上讲,它们只是普通函数定义中的一个语法技巧.类似于嵌套函数定义,lambda 形式可以从包含范围内引用变量： By popular demand, a few features commonly found in functional programming languages like Lisp have been added to Python. With the lambda keyword, small anonymous functions can be created. Here’s a function that returns the sum of its two arguments: lambda a, b: a+b. Lambda forms can be used wherever function objects are required. They are syntactically restricted to a single expression. Semantically, they are just syntactic sugar for a normal function definition. Like nested function definitions, lambda forms can reference variables from the containing scope:

>>> def make_incrementor(n):
...     return lambda x: x + n
...
>>> f = make_incrementor(42)
>>> f(0)
42
>>> f(1)
43

-4.7.6. 文档字符串 Documentation Strings

这里介绍文档字符串的概念和格式. Here are some conventions about the content and formatting of documentation strings.

第一行应该是关于对象用途的简介.简短起见,不用明确的陈述对象名或类型,因为它们可以从别的途径了解到（除非这个名字碰巧就是描述这个函数操作的动词）.这一行应该以大写字母开头,以句号结尾. The first line should always be a short, concise summary of the object’s purpose. For brevity, it should not explicitly state the object’s name or type, since these are available by other means (except if the name happens to be a verb describing a function’s operation). This line should begin with a capital letter and end with a period.

如果文档字符串有多行,第二行应该空出来,与接下来的详细描述明确分隔.接下来的文档应该有一或多段描述对象的调用约定、边界效应等. If there are more lines in the documentation string, the second line should be blank, visually separating the summary from the rest of the description. The following lines should be one or more paragraphs describing the object’s calling conventions, its side effects, etc.

Python的解释器不会从多行的文档字符串中去除缩进,所以必要的时候应当自己清除缩进.这符合通常的习惯.第一行之后的第一个非空行决定了整个文档的缩进格式.（我们不用第一行是因为它通常紧靠着起始的引号,缩进格式显示的不清楚.）留白"相当于"是字符串的起始缩进.每一行都不应该有缩进,如果有缩进的话,所有的留白都应该清除掉.留白的长度应当等于扩展制表符的宽度（通常是8个空格）. The Python parser does not strip indentation from multi-line string literals in Python, so tools that process documentation have to strip indentation if desired. This is done using the following convention. The first non-blank line after the first line of the string determines the amount of indentation for the entire documentation string. (We can’t use the first line since it is generally adjacent to the string’s opening quotes so its indentation is not apparent in the string literal.) Whitespace “equivalent” to this indentation is then stripped from the start of all lines of the string. Lines that are indented less should not occur, but if they occur all their leading whitespace should be stripped. Equivalence of whitespace should be tested after expansion of tabs (to 8 spaces, normally).

以下是一个多行文档字符串的示例: Here is an example of a multi-line docstring:

>>> 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. 插曲:编码类型 Intermezzo: Coding Style

既然您已经打算编写更长更复杂的Python程序块,是时候讨论下编码类型.许多语言都可以以不同的类型编写(简洁,格式化),其中一些更具可读性.让他人方便阅读您的代码是个不错的主意,采用一套漂亮的编码类型帮助巨大. Now that you are about to write longer, more complex pieces of Python, it is a good time to talk about coding style. Most languages can be written (or more concise, formatted) in different styles; some are more readable than others. Making it easy for others to read your code is always a good idea, and adopting a nice coding style helps tremendously for that.

对于Python,PEP8已经成为大多数项目都支持的风格指南;它推行良好的可读性和养眼的编码类型.每一位Python开发人员都应有所了解;以下是从中摘出的一些重要的关键点: For Python, PEP 8 has emerged as the style guide that most projects adhere to; it promotes a very readable and eye-pleasing coding style. Every Python developer should read it at some point; here are the most important points extracted for you:

• 使用4个空格缩进，不要使用tabs

4个空格是不大(易读)不小(允许深层嵌套)的折中缩进量.制表符会导致些困惑,也容易被忽略. 4 spaces are a good compromise between small indentation (allows greater nesting depth) and large indentation (easier to read). Tabs introduce confusion, and are best left out.

• 换行,以保证每行不超过79字符.

这可以帮助小屏幕用户，也可以在大屏幕上并排显示几个代码文件. This helps users with small displays and makes it possible to have several code files side-by-side on larger displays.

• 使用空行来分隔函数和类,以及函数内部的大块代码.

• 如果可能,在一行中添加相应的注释

• 使用文档字符串

• 操作符旁及逗号后使用空格,不要在在包围结构中直接使用: a = f(1, 2) + g(3, 4).

• 类与函数命名一致;惯例对类使用驼峰式写法,对于函数和方法采用小写和下划线结合写法.一直使用self作为第一个方法参数的名字(详情请查看初探类)

• 如果您打算在国际环境中使用,请不要使用奇怪的编码.Python默认编码UTF-8及纯ASCII为最佳选择.

• 同样的,如果在读取及维护代码时很少用到其它语言，请不要在标识符中使用非ASCII字符

附件Footnotes

1. 实际上，调用对像参考……

[1]Actually, call by object reference would be a better description, since if a mutable object is passed, the caller will see any changes the callee makes to it (items inserted into a list).

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