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Python Tutorial | |
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Besides the while statement just introduced, Python knows the usual control flow statements known from other languages, with some twists.
除了前面介绍的 while 语句，Python 还从别的语言中借鉴了一些流程控制功能，并有所改变。
Perhaps the most well-known statement type is the if statement. For example:
也许最有名的是 if 语句。例如：
>>> x = int(raw_input("Please enter an integer: "))
>>> 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 if ... elif ... elif ... sequence is a substitute for the switch or case statements found in other languages.
可能会有零到多个 elif 部分，else 是可选的。关键字“elif” 是“ else if ”的缩写，这个可以有效避免过深的缩进。if ... elif ... elif ... 序列用于替代其它语言中的 switch 或 case 语句。
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):
Python 中的 for 语句和 C 或 Pascal 中的略有不同。通常的循环可能会依据一个等差数值步进过程（如Pascal）或由用户来定义迭代步骤和中止条件（如 C ），Python 的 for 语句依据任意序列（链表或字符串）中的子项，按它们在序列中的顺序来进行迭代。例如（没有暗指）：
>>> # Measure some strings: ... a = ['cat', 'window', 'defenestrate'] >>> for x in a: ... print x, len(x) ... cat 3 window 6 defenestrate 12
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:
在迭代过程中修改迭代序列不安全（只有在使用链表这样的可变序列时才会有这样的情况）。如果你想要修改你迭代的序列（例如，复制选择项），你可以迭代它的复本。通常使用切片标识就可以很方便的做到这一点：
>>> 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']
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:
如果你需要一个数值序列，内置函数range()可能会很有用，它生成一个等差级数链表。
>>> 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, exactly 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(10) 生成了一个包含10个值的链表，它准确的用链表的索引值填充了这个长度为10的列表，所生成的链表中不包括范围中的结束值。也可以让range操作从另一个数值开始，或者可以指定一个不同的步进值（甚至是负数，有时这也被称为“步长”）：
>>> range(5, 10) [5, 6, 7, 8, 9] >>> range(0, 10, 3) [0, 3, 6, 9] >>> range(-10, -100, -30) [-10, -40, -70]
To iterate over the indices of a sequence, combine range() and len() as follows:
需要迭代链表索引的话，如下所示结合使 用range() 和 len() ：
>>> 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
The break statement, like in C, breaks out of the smallest enclosing for or while loop.
break 语句和 C 中的类似，用于跳出最近的一级 for 或 while 循环。
The continue statement, also borrowed from C, continues with the next iteration of the loop.
continue 语句是从 C 中借鉴来的，它表示循环继续执行下一次迭代。
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:
循环可以有一个 else 子句;它在循环迭代完整个列表（对于 for ）或执行条件为 false （对于 while ）时执行，但循环被 break 中止的情况下不会执行。以下搜索素数的示例程序演示了这个子句：
>>> 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
The pass statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example:
pass 语句什么也不做。它用于那些语法上必须要有什么语句，但程序什么也不做的场合，例如：
>>> while True: ... pass # Busy-wait for keyboard interrupt ...
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 b < n: ... print b, ... a, b = b, a+b ... >>> # Now call the function we just defined: ... fib(2000) 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
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. The first statement of the function body can optionally be a string literal; this string literal is the function's documentation string, or docstring.
关键字 def 引入了一个函数定义。在其后必须跟有函数名和包括形式参数的圆括号。函数体语句从下一行开始，必须是缩进的。函数体的第一行可以是一个字符串值，这个字符串是该函数的 (文档字符串（documentation string）)，也可称作 docstring 。
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 try to make a habit of it.
有些文档字符串工具可以在线处理或打印文档，或让用户交互的浏览代码;在代码中加入文档字符串是一个好的作法，应该养成这个习惯。
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 global symbol table, and then 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.
执行函数时会为局部变量引入一个新的符号表。所有的局部变量都存储在这个局部符号表中。引用参数时，会先从局部符号表中查找，然后是全局符号表，然后是内置命名表。因此，全局参数虽然可以被引用，但它们不能在函数中直接赋值（除非它们用 global 语句命名）。
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).4.1 When a function calls another function, a new local symbol table is created for that call.
函数引用的实际参数在函数调用时引入局部符号表，因此，实参总是传值调用（这里的值总是一个对象引用，而不是该对象的值）。4.2 一个函数被另一个函数调用时，一个新的局部符号表在调用过程中被创建。
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:
函数定义在当前符号表中引入函数名。作为用户定义函数，函数名有一个为解释器认可的类型值。这个值可以赋给其它命名，使其能够作为一个函数来使用。这就像一个重命名机制：
>>> fib <function fib at 10042ed0> >>> f = fib >>> f(100) 1 1 2 3 5 8 13 21 34 55 89
You might object that fib is not a function but a procedure. In
Python, like in C, procedures are just functions that don't return a
value. In fact, technically speaking, procedures 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:
你可能认为fib不是一个函数（ function ），而是一个过程（ procedure ）。Python 和 C 一样，过程只是一个没有返回值的函数。实际上，从技术上讲，过程也有一个返回值，虽然是一个不讨人喜欢的。这个值被称为 None （这是一个内置命名）。如果一个值只是 None 的话，通常解释器不会写一个 None 出来，如果你真想要查看它的话，可以这样做：
>>> print fib(0) None
It is simple to write a function that returns a list of the numbers of the Fibonacci series, instead of printing it:
以下示例演示了如何从函数中返回一个包含菲波那契数列的数值链表，而不是打印它：
>>> 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 b < n: ... result.append(b) # see below ... a, b = b, a+b ... return result ... >>> f100 = fib2(100) # call it >>> f100 # write the result [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
This example, as usual, demonstrates some new Python features:
和以前一样，这个例子演示了一些新的 Python 功能：
None.
Falling off the end of a procedure also returns None.
return 语句从函数中返回一个值，不带表达式的 return 返回 None。过程结束后也会返回 None 。
result.append(b) 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, as discussed later
in this tutorial.)
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 + [b]", but more
efficient.
语句 result.append(b) 称为链表对象 result 的一个方法（ method ）。方法是一个“属于”某个对象的函数，它被命名为 obj.methodename ，这里的 obj 是某个对象（可能是一个表达式），methodename 是某个在该对象类型定义中的方法的命名。不同的类型定义不同的方法。不同类型可能有同样名字的方法，但不会混淆。（当你定义自己的对象类型和方法时，可能会出现这种情况，本指南后面的章节会介绍如何使用类型）。示例中演示的 append()方法由链表对象定义，它向链表中加入一个新元素。在示例中它等同于""result = result + [b]""，不过效率更高。
It is also possible to define functions with a variable number of arguments. There are three forms, which can be combined.
有时需要定义参数个数可变的函数。有三个方法可以达到目的，我们可以组合使用它们。
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:
最有用的形式是给一个或多个参数指定默认值。这样创建的函数可以用较少的参数来调用。例如：
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
This function can be called either like this:
ask_ok('Do you really want to quit?') or like this:
ask_ok('OK to overwrite the file?', 2).
这个函数还可以用以下的方式调用：ask_ok('Do you really want
to quit?')，或者像这样：ask_ok('OK to overwrite the file?',
2)。
This example also introduces the in keyword. This tests whether or not a sequence contains a certain value.
这个示例还介绍了关键字 in 。它检测一个序列中是否包含某个给定的值。
The default values are evaluated at the point of function definition in the defining scope, so that
默认值在函数定义段被解析，如下所示：
i = 5
def f(arg=i):
print arg
i = 6
f()
will print 5.
以上代码会打印5。
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:
重要警告：默认值只会解析一次。当默认值是一个可变对象，诸如链表、字典或大部分类实例时，会产生一些差异。例如，以下函数在后继的调用中会累积它的参数值：
def f(a, L=[]):
L.append(a)
return L
print f(1)
print f(2)
print f(3)
This will print
这会打印出：
[1] [1, 2] [1, 2, 3]
If you don't want the default to be shared between subsequent calls, you can write the function like this instead:
如果你不想在不同的函数调用之间共享参数默认值，可以如下面的实例一样编写函数：
def f(a, L=None):
if L is None:
L = []
L.append(a)
return L
Functions can also be called using keyword arguments of the form "keyword = value". For instance, the following function:
函数可以通过关键字参数的形式来调用，形如"keyword = value"。例如，以下的函数：
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, "!"
could be called in any of the following ways:
可以用以下的任一方法调用：
parrot(1000)
parrot(action = 'VOOOOOM', voltage = 1000000)
parrot('a thousand', state = 'pushing up the daisies')
parrot('a million', 'bereft of life', 'jump')
but the following calls would all be invalid:
不过以下几种调用是无效的：
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
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:
通常，参数列表中的每一个关键字都必须来自于形式参数，每个参数都有对应的关键字。形式参数有没有默认值并不重要。实际参数不能一次赋多个值——形式参数不能在同一次调用中同时使用位置和关键字绑定值。这里有一个例子演示了在这种约束下所出现的失败情况：
>>> 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'
When a final formal parameter of the form **name is
present, it receives a dictionary containing all keyword arguments
whose keyword doesn't correspond 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:
引入一个形如 **name 的参数时，它接收一个 字典 ，该字典包含了所有未出现在形式参数列表中的关键字参数。这里可能还会组合使用一个形如 *name 的形式参数，它接收一个元组（下一节中会详细介绍），包含了所有没有出现在形式参数列表中的参数值。（*name 必须在 **name 之前出现） 例如，我们这样定义一个函数：
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 = keywords.keys()
keys.sort()
for kw in keys: print kw, ':', keywords[kw]
It could be called like this:
它可以像这样调用：
cheeseshop('Limburger', "It's very runny, sir.",
"It's really very, VERY runny, sir.",
client='John Cleese',
shopkeeper='Michael Palin',
sketch='Cheese Shop Sketch')
and of course it would print:
当然它会按如下内容打印：
-- 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 sort() method of the list of keyword argument
names is called before printing the contents of the keywords
dictionary; if this is not done, the order in which the arguments are
printed is undefined.
注意sort()方法在关键字字典内容打印前被调用，否则的话，打印参数时的顺序是未定义的。
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. Before the variable number of arguments, zero or more normal arguments may occur.
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。在这些可变个数的参数之前，可以有零到多个普通的参数：
def fprintf(file, format, *args):
file.write(format % args)
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:
另有一种相反的情况: 当你要传递的参数已经是一个列表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() 需要要独立的 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:
>>> 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]
By popular demand, a few features commonly found in functional programming languages and 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:
出于实际需要，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，可以创建短小的匿名函数。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：
>>> def make_incrementor(n): ... return lambda x: x + n ... >>> f = make_incrementor(42) >>> f(0) 42 >>> f(1) 43
There are emerging conventions about the content and formatting of documentation strings.
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.
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。
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.
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。
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).
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）。
Here is an example of a multi-line docstring:
以下是一个多行文档字符串的示例：
>>> 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.
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