Tracing Python Code to Locate Issues
In other programming languages like Java or C#, stepping through code to isolate problems is straightforward with the help of IDEs. Can Python offer a similar debugging method?
Solution: The Python Debugger (pdb)
Python features a built-in debugger called pdb that facilitates code tracing. To use pdb, launch your Python program with the command:
python -m pdb myscript.py
Upon launching, you can utilize the following pdb commands for debugging:
- b: Set a breakpoint
- c: Continue execution until reaching a breakpoint
- s: Step through the code
- n: Advance to the next line of code
- l: Display source code for the current file
- u: Move up the stack frame
- d: Move down the stack frame
- p: Evaluate an expression in the current context
For those preferring a graphical interface, IDEs such as Pydev, Wing IDE, or PyCharm offer GUI debuggers. While Wing and PyCharm are paid products, they have free versions available.
The above is the detailed content of How Can I Effectively Debug Python Code?. For more information, please follow other related articles on the PHP Chinese website!
How to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AMThis tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th
How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PMThis 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
How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PMThis 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: Part 1Mar 08, 2025 am 09:39 AMSerialization 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
Mathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AMPython'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
Professional Error Handling With PythonMar 04, 2025 am 10:58 AMIn this tutorial you'll learn how to handle error conditions in Python from a whole system point of view. Error handling is a critical aspect of design, and it crosses from the lowest levels (sometimes the hardware) all the way to the end users. If y
What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PMThe 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
Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AMThis 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
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
SublimeText3 Mac version
God-level code editing software (SublimeText3)
SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.
Atom editor mac version download
The most popular open source editor
mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),
SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.
