What is the method of debugging in Python?
Test code used in this article:
from torchvision import transforms from torchvision.datasets import FashionMNIST import os os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE" #数据集准备 train_data = FashionMNIST( root = "./data/FashionMNIST", train = True, transform = transforms.ToTensor(), download = True #如果没下载数据,就下载数据;如果已经下载好,就换为False ) test_data = FashionMNIST( root = "./data/FashionMNIST", train = False, transform = transforms.ToTensor(), download = True #如果没下载数据,就下载数据;如果已经下载好,就换为False ) train_data_x=train_data.data train_data_y=train_data.targets test_data_x=test_data.data test_data_y=test_data.targets print(train_data_x.shape) print(train_data_y.shape) print(type(train_data_x)) print(type(train_data_y)) print(test_data_x.shape) print(test_data_y.shape) def function1(x): for i in range(x): print(i) function1(7)
1. Introduction to debug environment
Click this crawler to start debugging
in Before debugging, we need to set breakpoints: (Several settings will do)
After entering debug, the lower left corner:
1) You can see the existing variables in the debugger:
2) In the console, you can see the step-by-step debugging process, and the output results will be printed in it:
2. Introduction to the debug button
#1) step over shortcut key: F8
2) step into shortcut key: F7
3) step into my code shortcut key: alt shift F7
4) step out shortcut key: shift F8
2.1. step into: single-step execution (when encountering a function, it is also a single step)
Pay attention to the change of the blue line (the blue line means that it is about to be debugged, but it is still No debugging)
2.2. Step over: single-step execution (run all functions when encountering them)
Compared with step over, this is the difference between execution in the function: ( step over is executed directly)2.3, step into my code: (jump directly to the next breakpoint)
This is easy to understand. I have three breakpoints here, so I will debug three times and then end:
is the single-click function inside the function. When debugging step by step, use step out to complete the execution at once and return to the previous layer function.
After using it, the entire function is executed directly, but the process is not ended
Look at the blue line, returning to the previous layer of function
The above is the detailed content of What is the method of debugging in Python?. For more information, please follow other related articles on the PHP Chinese website!

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

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

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

Hot Topics



VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.

In VS Code, you can run the program in the terminal through the following steps: Prepare the code and open the integrated terminal to ensure that the code directory is consistent with the terminal working directory. Select the run command according to the programming language (such as Python's python your_file_name.py) to check whether it runs successfully and resolve errors. Use the debugger to improve debugging efficiency.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

VS Code is available on Mac. It has powerful extensions, Git integration, terminal and debugger, and also offers a wealth of setup options. However, for particularly large projects or highly professional development, VS Code may have performance or functional limitations.

The key to running Jupyter Notebook in VS Code is to ensure that the Python environment is properly configured, understand that the code execution order is consistent with the cell order, and be aware of large files or external libraries that may affect performance. The code completion and debugging functions provided by VS Code can greatly improve coding efficiency and reduce errors.

Golang is more suitable for high concurrency tasks, while Python has more advantages in flexibility. 1.Golang efficiently handles concurrency through goroutine and channel. 2. Python relies on threading and asyncio, which is affected by GIL, but provides multiple concurrency methods. The choice should be based on specific needs.
