


Today in this article we will learn about finally exception handling in python exception handling. First we need to understand the finally statement in python. tryfinally will It will be explained and analyzed with examples in the following article.
First of all, we need to know that the try-finally statement will execute the last code regardless of whether an exception occurs.
Just like the following:
try: <语句> finally: <语句> #退出try时总会执行 raise
Next, let’s give an example:
#!/usr/bin/python # -*- coding: UTF-8 -*- try: fh = open("testfile", "w") fh.write("这是一个测试文件,用于测试异常!!") finally: print "Error: 没有找到文件或读取文件失败"
If the opened file does not have writable permissions, the output will be as follows:
$ python test.py Error: 没有找到文件或读取文件失败
The same example can also be written as follows:
#!/usr/bin/python # -*- coding: UTF-8 -*- try: fh = open("testfile", "w") try: fh.write("这是一个测试文件,用于测试异常!!") finally: print "关闭文件" fh.close() except IOError: print "Error: 没有找到文件或读取文件失败"
When an exception is thrown in the try block, the finally block code is executed immediately.
After all statements in the finally block are executed, the exception is triggered again and the except block code is executed.
The content of the parameter is different from the exception.
In this article, we explain what the try-finally statement is. If you don’t understand, you can give it a try. After all, hands-on practice is the best way to verify what you have learned. Finally, I hope this article can bring some help to you who are learning python.
For more related knowledge, please visit the Python tutorial column on the php Chinese website.
The above is the detailed content of What is the pythontry-finally statement? What role can it play?. For more information, please follow other related articles on the PHP Chinese website!

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

The article discusses the role of virtual environments in Python, focusing on managing project dependencies and avoiding conflicts. It details their creation, activation, and benefits in improving project management and reducing dependency issues.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

WebStorm Mac version
Useful JavaScript development tools

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)
