Home Backend Development Python Tutorial python with statement 进行文件操作指南

python with statement 进行文件操作指南

Jun 16, 2016 am 08:42 AM
python with

由于之前有一个项目老是要打开文件,然后用pickle.load(file),再处理。。。最后要关闭文件,所以觉得有点繁琐,代码也不简洁。所以向python with statement寻求解决方法。

在网上看到一篇文章:http://effbot.org/zone/python-with-statement.htm是介绍with 的,参考着例子进行了理解。

如果经常有这么一些代码段的话,可以用一下几种方法改进:

代码段:

set thing up
try:
  do something
except :
  handle exception
finally:
  tear thing down
Copy after login

案例1:

假如现在要实现这么一个功能,就是打开文件,从文件里面读取数据,然后打印到终端,之后关闭文件。

那么从逻辑上来说,可以抽取“打印到终端”为数据处理部分,应该可以独立开来作为一个函数。其他像打开、关闭文件应该是一起的。

文件名为:for_test.txt

方法1:

用函数,把公共的部分抽取出来。

#!/usr/bin/env python 
from __future__ import with_statement  
filename = 'for_test.txt' 
def output(content): 
  print content 
#functio solution 
def controlled_execution(func): 
  #prepare thing 
  f = None 
  try: 
    #set thing up 
    f = open(filename, 'r') 
    content = f.read() 
    if not callable(func): 
      return 
    #deal with thing  
    func(content) 
  except IOError, e: 
    print 'Error %s' % str(e) 
  finally: 
    if f:  
      #tear thing down 
      f.close() 
def test(): 
  controlled_execution(output) 
test() 
Copy after login


方法2:

用yield实现一个只产生一项的generator。通过for - in 来循环。

代码片段如下:

#yield solution 
def controlled_execution(): 
  f = None 
  try: 
    f = open(filename, 'r') 
    thing = f.read() 
    #for thing in f: 
    yield thing 
  except IOError,e: 
    print 'Error %s' % str(e) 
  finally: 
    if f:  
      f.close() 
def test2(): 
  for content in controlled_execution(): 
    output(content) 
Copy after login

方法3:

用类的方式加上with实现。

代码片段如下:

#class solution 
class controlled_execution(object): 
  def __init__(self): 
    self.f = None 
  def __enter__(self): 
    try: 
      f = open(filename, 'r') 
      content = f.read() 
      return content 
    except IOError ,e: 
      print 'Error %s' % str(e) 
      #return None 
  def __exit__(self, type, value, traceback): 
    if self.f: 
      print 'type:%s, value:%s, traceback:%s' % \ 
          (str(type), str(value), str(traceback)) 
      self.f.close() 
def test3(): 
  with controlled_execution() as thing: 
    if thing: 
      output(thing) 
 
Copy after login

方法4:

用with实现。不过没有exception handle 的功能。

def test4(): 
  with open(filename, 'r') as f: 
    output(f.read()) 
 
  print f.read() 
Copy after login

 最后一句print是用来测试f是否已经被关闭了。

    最后总结一下,写这篇文章的目的主要是受了一句话的刺激:“使用语言的好特性,不要使用那些糟糕的特性”!python真是有很多很优雅的好特性,路漫漫其修远兮,吾将上下而求索。。。

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
Will R.E.P.O. Have Crossplay?
1 months ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

PHP and Python: Code Examples and Comparison PHP and Python: Code Examples and Comparison Apr 15, 2025 am 12:07 AM

PHP and Python have their own advantages and disadvantages, and the choice depends on project needs and personal preferences. 1.PHP is suitable for rapid development and maintenance of large-scale web applications. 2. Python dominates the field of data science and machine learning.

Python vs. JavaScript: Community, Libraries, and Resources Python vs. JavaScript: Community, Libraries, and Resources Apr 15, 2025 am 12:16 AM

Python and JavaScript have their own advantages and disadvantages in terms of community, libraries and resources. 1) The Python community is friendly and suitable for beginners, but the front-end development resources are not as rich as JavaScript. 2) Python is powerful in data science and machine learning libraries, while JavaScript is better in front-end development libraries and frameworks. 3) Both have rich learning resources, but Python is suitable for starting with official documents, while JavaScript is better with MDNWebDocs. The choice should be based on project needs and personal interests.

How is the GPU support for PyTorch on CentOS How is the GPU support for PyTorch on CentOS Apr 14, 2025 pm 06:48 PM

Enable PyTorch GPU acceleration on CentOS system requires the installation of CUDA, cuDNN and GPU versions of PyTorch. The following steps will guide you through the process: CUDA and cuDNN installation determine CUDA version compatibility: Use the nvidia-smi command to view the CUDA version supported by your NVIDIA graphics card. For example, your MX450 graphics card may support CUDA11.1 or higher. Download and install CUDAToolkit: Visit the official website of NVIDIACUDAToolkit and download and install the corresponding version according to the highest CUDA version supported by your graphics card. Install cuDNN library:

Detailed explanation of docker principle Detailed explanation of docker principle Apr 14, 2025 pm 11:57 PM

Docker uses Linux kernel features to provide an efficient and isolated application running environment. Its working principle is as follows: 1. The mirror is used as a read-only template, which contains everything you need to run the application; 2. The Union File System (UnionFS) stacks multiple file systems, only storing the differences, saving space and speeding up; 3. The daemon manages the mirrors and containers, and the client uses them for interaction; 4. Namespaces and cgroups implement container isolation and resource limitations; 5. Multiple network modes support container interconnection. Only by understanding these core concepts can you better utilize Docker.

MiniOpen Centos compatibility MiniOpen Centos compatibility Apr 14, 2025 pm 05:45 PM

MinIO Object Storage: High-performance deployment under CentOS system MinIO is a high-performance, distributed object storage system developed based on the Go language, compatible with AmazonS3. It supports a variety of client languages, including Java, Python, JavaScript, and Go. This article will briefly introduce the installation and compatibility of MinIO on CentOS systems. CentOS version compatibility MinIO has been verified on multiple CentOS versions, including but not limited to: CentOS7.9: Provides a complete installation guide covering cluster configuration, environment preparation, configuration file settings, disk partitioning, and MinI

How to operate distributed training of PyTorch on CentOS How to operate distributed training of PyTorch on CentOS Apr 14, 2025 pm 06:36 PM

PyTorch distributed training on CentOS system requires the following steps: PyTorch installation: The premise is that Python and pip are installed in CentOS system. Depending on your CUDA version, get the appropriate installation command from the PyTorch official website. For CPU-only training, you can use the following command: pipinstalltorchtorchvisiontorchaudio If you need GPU support, make sure that the corresponding version of CUDA and cuDNN are installed and use the corresponding PyTorch version for installation. Distributed environment configuration: Distributed training usually requires multiple machines or single-machine multiple GPUs. Place

How to update PyTorch to the latest version on CentOS How to update PyTorch to the latest version on CentOS Apr 14, 2025 pm 06:15 PM

Updating PyTorch to the latest version on CentOS can follow the following steps: Method 1: Updating pip with pip: First make sure your pip is the latest version, because older versions of pip may not be able to properly install the latest version of PyTorch. pipinstall--upgradepip uninstalls old version of PyTorch (if installed): pipuninstalltorchtorchvisiontorchaudio installation latest

How to choose the PyTorch version on CentOS How to choose the PyTorch version on CentOS Apr 14, 2025 pm 06:51 PM

When installing PyTorch on CentOS system, you need to carefully select the appropriate version and consider the following key factors: 1. System environment compatibility: Operating system: It is recommended to use CentOS7 or higher. CUDA and cuDNN:PyTorch version and CUDA version are closely related. For example, PyTorch1.9.0 requires CUDA11.1, while PyTorch2.0.1 requires CUDA11.3. The cuDNN version must also match the CUDA version. Before selecting the PyTorch version, be sure to confirm that compatible CUDA and cuDNN versions have been installed. Python version: PyTorch official branch

See all articles