search
HomeBackend DevelopmentPython TutorialAnalysis of the comparison principle of Python's built-in comparison function cmp

Analysis of the comparison principle of Pythons built-in comparison function cmp

cmp(x, y): Compares two objects. If the former is less than the latter, it returns -1, if they are equal, it returns 0, and if it is greater than the latter, it returns 1.

Python's cmp comparison function comparison principle

Python's cmp function You can compare between the same type or between different data types. Then determine the comparison size based on the return value of Python's cmp comparison function.

>>> list1, list2 = [123, 'xyz'], [456, 'abc']
>>> cmp(list1, list2)
-1
>>> cmp(list2, list1)
1
>>> list3 = list2 + [789]
>>> list3
[456, 'abc', 789]
>>> cmp(list2, list3)
-1

Observing several comparisons of the cmp function above, we can summarize:

Python's cmp comparison function, if we are comparing two similar objects, the comparison operation is very intuitive.

Comparison of numbers and strings, directly compare their values.

For comparison of sequence types, the methods are similar. Python tries to produce fair results when two objects are basically incomparable. For example, when two objects have no relationship, or when the two types have no functions for comparison at all, Python can only make conclusions based on "logic". Algorithm logic of comparison:

1. Compare the elements of the two lists.

2. If the compared elements are of the same type, compare their values ​​and return the result.

3. If the two elements are not of the same type type, check whether they are numbers.

a. If they are numbers, perform the necessary numeric cast, and then compare.

b. If the elements of one side are numbers, the elements of the other side are "big" (numbers) is "smallest")

c. Otherwise, compare by alphabetical order of type names.

4. If one list reaches the end first, then the other, longer list is "bigger".

5. If we If the elements of both lists are exhausted and all elements are equal, then the result is a tie, which means returning a 0.

This is the comparison principle of Python's cmp function

Statement
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
How to Use Python to Find the Zipf Distribution of a Text FileHow to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This 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?How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

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

How to Perform Deep Learning with TensorFlow or PyTorch?How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

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

Mathematical Modules in Python: StatisticsMathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

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

Serialization and Deserialization of Python Objects: Part 1Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

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

What are some popular Python libraries and their uses?What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

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

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationScraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

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

How to Create Command-Line Interfaces (CLIs) with Python?How to Create Command-Line Interfaces (CLIs) with Python?Mar 10, 2025 pm 06:48 PM

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.

See all articles

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

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

DVWA

DVWA

Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version