使用“ open（）”和“ with open（）”读取文件

Question

我知道有很多关于阅读python文件的文章和回答的问题。但是我仍然想知道是什么使python具有多种方法来完成相同的任务。我只想知道，使用这两种方法对性能有何影响？

Answer 1

usingwith语句不是为了提高性能，with只要您执行与usingwith语句将自动执行的相同的清除活动，我认为与using语句不存在任何性能提升或损失。

当您将with带有open功能的语句一起使用时，不需要最后关闭文件，因为with它将自动为您关闭文件。

此外，with语句不仅用于打开文件，还与上下文管理器结合使用。基本上，如果您有一个要确保在完成操作后便将其清除或发生某种错误的对象，则可以将其定义为上下文管理器，并且with语句将在进入和退出时调用__enter__()和__exit__()方法with块。根据PEP
0343
-

该PEPwith在Python语言中添加了新的语句“ ”，从而可以排除try / finally语句的标准用法。

在此PEP中，上下文管理器提供__enter__()和__exit__()方法，这些方法在进入with语句主体和从with语句主体退出时被调用。

另外，对使用with和不使用它的性能进行测试-

In [14]: def foo():
   ....:     f = open('a.txt','r')
   ....:     for l in f:
   ....:         pass
   ....:     f.close()
   ....:

In [15]: def foo1():
   ....:     with open('a.txt','r') as f:
   ....:         for l in f:
   ....:             pass
   ....:

In [17]: %timeit foo()
The slowest run took 41.91 times longer than the fastest. This could mean that an intermediate result is being cached
10000 loops, best of 3: 186 µs per loop

In [18]: %timeit foo1()
The slowest run took 206.14 times longer than the fastest. This could mean that an intermediate result is being cached
10000 loops, best of 3: 179 µs per loop

In [19]: %timeit foo()
The slowest run took 202.51 times longer than the fastest. This could mean that an intermediate result is being cached
10000 loops, best of 3: 180 µs per loop

In [20]: %timeit foo1()
10000 loops, best of 3: 193 µs per loop

In [21]: %timeit foo1()
10000 loops, best of 3: 194 µs per loop