Python’s with statement provides a very convenient way of dealing with the situation where you have to do a setup and teardown to make something happen. A very good example for this is the situation where you want to gain a handler to a file, read data from the file and the close the file handler. 有一些任务,可能事先需要设置,事后做清理工作。对于这种场景,Python的with语句提供了一种非常方便的处理方式。一个很好的例子是文件处理,你需要获取一个文件句柄,从文件中读取数据,然后关闭文件句柄。 Without the with statement, one would write something along the lines of: 如果不用with语句,代码如下:

1
2
3
file = open("/tmp/foo.txt")
data = file.read()
file.close()

There are two annoying things here. First, you end up forgetting to close the file handler. The second is how to handle exceptions that may occur once the file handler has been obtained. One could write something like this to get around this: 这里有两个问题。一是可能忘记关闭文件句柄;二是文件读取数据发生异常,没有进行任何处理。下面是处理异常的加强版本:

1
2
3
4
5
file = open("/tmp/foo.txt")
try:
    data = file.read()
finally:
    file.close()

While this works well, it is unnecessarily verbose. This is where with is useful. The good thing about with apart from the better syntax is that it is very good handling exceptions. The above code would look like this, when using with: 虽然这段代码运行良好,但是太冗长了。这时候就是with一展身手的时候了。除了有更优雅的语法,with还可以很好的处理上下文环境产生的异常。下面是with版本的代码:

1
2
with open("/tmp/foo.txt") as file:
    data = file.read()

with如何工作?

while this might look like magic, the way Python handles with is more clever than magic. The basic idea is that the statement after with has to evaluate an object that responds to an __enter__() as well as an __exit__() function. 这看起来充满魔法,但不仅仅是魔法,Python对with的处理还很聪明。基本思想是with所求值的对象必须有一个__enter__()方法,一个__exit__()方法。 After the statement that follows with is evaluated, the __enter__() function on the resulting object is called. The value returned by this function is assigned to the variable following as. After every statement in the block is evaluated, the __exit__() function is called. 紧跟with后面的语句被求值后,返回对象的__enter__()方法被调用,这个方法的返回值将被赋值给as后面的变量。当with后面的代码块全部被执行完之后,将调用前面返回对象的__exit__()方法。 This can be demonstrated with the following example: 下面例子可以具体说明with如何工作:

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
#!/usr/bin/env python
# with_example01.py
 
 
class Sample:
    def __enter__(self):
        print "In __enter__()"
        return "Foo"
 
    def __exit__(self, type, value, trace):
        print "In __exit__()"
 
 
def get_sample():
    return Sample()
 
 
with get_sample() as sample:
    print "sample:", sample

When executed, this will result in: 运行代码,输出如下

1
2
3
4
bash-3.2$ ./with_example01.py
In __enter__()
sample: Foo
In __exit__()

As you can see, The __enter__() function is executed The value returned by it - in this case "Foo" is assigned to sample The body of the block is executed, thereby printing the value of sample ie. "Foo" The __exit__() function is called. What makes with really powerful is the fact that it can handle exceptions. You would have noticed that the __exit__() function for Sample takes three arguments - val, type and trace. These are useful in exception handling. Let’s see how this works by modifying the above example. 正如你看到的, 1. __enter__()方法被执行 2. __enter__()方法返回的值 - 这个例子中是"Foo",赋值给变量'sample' 3. 执行代码块,打印变量"sample"的值为 "Foo" 4. __exit__()方法被调用 with真正强大之处是它可以处理异常。可能你已经注意到Sample类的__exit__方法有三个参数- val, type 和 trace。 这些参数在异常处理中相当有用。我们来改一下代码,看看具体如何工作的。

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
#!/usr/bin/env python
# with_example02.py
 
 
class Sample:
    def __enter__(self):
        return self
 
    def __exit__(self, type, value, trace):
        print "type:", type
        print "value:", value
        print "trace:", trace
 
    def do_something(self):
        bar = 1/0
        return bar + 10
 
with Sample() as sample:
    sample.do_something()

Notice how in this example, instead of get_sample(), with takes Sample(). It does not matter, as long as the statement that follows with evaluates to an object that has an __enter__() and __exit__() functions. In this case, Sample()’s __enter__() returns the newly created instance of Sample and that is what gets passed to sample. 这个例子中,with后面的get_sample()变成了Sample()。这没有任何关系,只要紧跟with后面的语句所返回的对象有__enter__()和__exit__()方法即可。此例中,Sample()的__enter__()方法返回新创建的Sample对象,并赋值给变量sample。 When executed: 代码执行后:

1
2
3
4
5
6
7
8
9
10
bash-3.2$ ./with_example02.py
type: <type 'exceptions.ZeroDivisionError'>
value: integer division or modulo by zero
trace: <traceback object at 0x1004a8128>
Traceback (most recent call last):
  File "./with_example02.py", line 19, in <module>
    sample.do_something()
  File "./with_example02.py", line 15, in do_something
    bar = 1/0
ZeroDivisionError: integer division or modulo by zero

Essentially, if there are exceptions being thrown from anywhere inside the block, the __exit__() function for the object is called. As you can see, the type, value and the stack trace associated with the exception thrown is passed to this function. In this case, you can see that there was a ZeroDivisionError exception being thrown. People implementing libraries can write code that clean up resources, close files etc. in their __exit__() functions. 实际上,在with后面的代码块抛出任何异常时,__exit__()方法被执行。正如例子所示,异常抛出时,与之关联的type,value和stack trace传给__exit__()方法,因此抛出的ZeroDivisionError异常被打印出来了。开发库时,清理资源,关闭文件等等操作,都可以放在__exit__方法当中。 Thus, Python’s with is a nifty construct that makes code a little less verbose and makes cleaning up during exceptions a bit easier. 因此,Python的with语句是提供一个有效的机制,让代码更简练,同时在异常产生时,清理工作更简单。

理解python的with语句的更多相关文章

  1. 转: 理解Python的With语句

    Python’s with statement provides a very convenient way of dealing with the situation where you have ...

  2. 深入理解python with语句

    python的with语句相当于try.....finally,它是如何实现的呢?下面就结合范例和伪指令的实现来分析一下. with语句会汇编成:先调用with语句后面的表达式(open(...)), ...

  3. 用一个简单的例子来理解python高阶函数

    ============================ 用一个简单的例子来理解python高阶函数 ============================ 最近在用mailx发送邮件, 写法大致如 ...

  4. 深入理解 Python 异步编程(上)

    http://python.jobbole.com/88291/ 前言 很多朋友对异步编程都处于"听说很强大"的认知状态.鲜有在生产项目中使用它.而使用它的同学,则大多数都停留在知 ...

  5. 完全理解 Python 迭代对象、迭代器、生成器

    完全理解 Python 迭代对象.迭代器.生成器 2017/05/29 · 基础知识 · 9 评论 · 可迭代对象, 生成器, 迭代器 分享到: 原文出处: liuzhijun    本文源自RQ作者 ...

  6. [转]深刻理解Python中的元类(metaclass)以及元类实现单例模式

    使用元类 深刻理解Python中的元类(metaclass)以及元类实现单例模式 在看一些框架源代码的过程中碰到很多元类的实例,看起来很吃力很晦涩:在看python cookbook中关于元类创建单例 ...

  7. python assert 断言语句的作用

    python assert 断言语句的作用 assert语句的应用场景 使用assert语句是一个很好的习惯. 我们在编写代码的时候, 不知道程序会在什么时候崩溃, 与其让它在深度运行时崩溃, 不如预 ...

  8. 深入理解Python中的yield和send

    send方法和next方法唯一的区别是在执行send方法会首先把上一次挂起的yield语句的返回值通过参数设定,从而实现与生成器方法的交互. 但是需要注意,在一个生成器对象没有执行next方法之前,由 ...

  9. 理解 python 装饰器

    变量 name = 'world' x = 3 变量是代表某个值的名字 函数 def hello(name): return 'hello' + name hello('word) hello wor ...

随机推荐

  1. 不使用插件实现对WordPress默认编辑器的增强

    四处寻觅无果.无意看了一下wordpress官方的API函数.苍天有眼啊!原来,后台的编辑器可以插入很多增强功能.果断卸载掉CK and SyntaxHighlighter编辑器插件.事实上,Word ...

  2. 常见的JavaScript函数

    JavaScript函数一共可分为5类:常规函数.数组函数.日期函数.数学函数和字符串函数. (1)常规函数(9个) alert函数:显示一个警告对话框,包括一个“确定”按钮. confirm函数:显 ...

  3. SPSS数据分析—加权最小二乘法

    标准的线性回归模型的假设之一是因变量方差齐性,即因变量或残差的方差不随自身预测值或其他自变量的值变化而变化.但是有时候,这种情况会被违反,称为异方差性,比如因变量为储蓄额,自变量为家庭收入,显然高收入 ...

  4. Lua 与 Redis

    Lua 与 Redis 标签: Java与NoSQL 从 2.6版本 起, Redis 开始支持 Lua 脚本 让开发者自己扩展 Redis - 案例-实现访问频率限制: 实现访问者 $ip 在一定的 ...

  5. css3实现颜色渐变以及兼容性处理

    有时我们会看到网站上的一些图片是渐变色的,这些图片有的是ui设计出来的,有的则是直接通过css3制作出来的.下面就讲一下css3实现渐变色的方法,以及在各个浏览器上的兼容性. CSS3 Gradien ...

  6. HashMap,LinkedHashMap,TreeMap的区别

    Map主要用于存储健值对,根据键得到值,因此不允许键重复(重复了覆盖了),但允许值重复. Hashmap 是一个最常用的Map,它根据键的HashCode 值存储数据,根据键可以直接获取它的值,具有很 ...

  7. caffe安装过程中遇到的问题以及解决方法

    1. 在安装依赖库的时候,遇到: @gxjun-Latitude-E5440:~$ sudo apt-get install libatlas-base-dev 正在读取软件包列表... 完成 正在分 ...

  8. Redis学习笔记二

    学习Redis添加Object时,由于Redis只能存取字符串String,对于其它数据类型形容:Int,long,double,Date等不提供支持,因而需要设计到对象的序列化和反序列化.java序 ...

  9. chrome经常崩溃解决过程

    之前chrome常崩溃,也没有找到原因,就将就着用吧,一直用到今天,今天连续几次崩了,突然想到,难道是因为我访问的域名没有解析(能想到这个,是因为今天分配公司域名测试的时候常输错),于是就输入一个不存 ...

  10. Process Explorer使用图文教程

    这是一款由Sysinternals开发的Windows系统和应用程序监视工具,目前Sysinternals已经被微软收购,此款不仅结合了文件监视和注册表监视两个工具的功能,还增加了多项重要的增强功能, ...