Programming News and Topics: Latest News on Computer Programming from Techminis

A naukri.com initiative

New

Home

Programming News

RealPython

Image Credit: RealPython

How to Find an Absolute Value in Python

Learn how to work with absolute values in Python using the built-in abs() function for numbers, arrays, and custom objects.
Implement the absolute value function from scratch, use abs() with numbers, and customize its behavior for data types like NumPy arrays and pandas Series.
Python's abs() function efficiently handles integers, floating-point numbers, complex numbers, and more.
NumPy and pandas extend the abs() function to work directly with arrays and Series.
Customize the behavior of abs() for your own data types by implementing the .__abs__() method.
The abs() function can process fractions and decimals from Python's standard library.
Absolute value helps determine the magnitude of an object, like a number or vector, regardless of direction.
Absolute value function in Python can be implemented using conditional statements or mathematical operations.
Visualizing absolute value as the distance from the origin on a number line or in multi-dimensional space like vectors.
Understand how to calculate the length or magnitude of vectors using Euclidean norm.

Read Full Article

2 Likes

Medium

265

Image Credit: Medium

4D Hairy Ball and the Woven Continuum Theory with Numpy Proof

The Woven Continuum Theory explores resolving topological obstructions in 3D systems by projecting higher-dimensional fields, such as in the 4D Hairy Ball theorem where singularities may be addressed in 4D or higher dimensions.
The theory combines results like the parallelizability of S³, explicit recursion schemes, and fractal dynamics to unify topology, physics, and metaphysics under a balance paradigm.
By embedding the 3-sphere S³ into 4D, a continuous, nowhere-zero vector field can cover what appears as zeros in 3D, presenting a topological foundation for '4D weaving.'
The iterative correction formula in the Woven Continuum Theory continually corrects emergent zeros in a 3D field by drawing on an extra 4th dimension, ensuring a smooth passage through higher dimensions.
Fractal dynamics and the use of 4D constructions like the Hopf fibration and quaternionic algebra play key roles in the iterative weaving procedure to avoid zeros in the field.
The theory's application extends to addressing concrete areas like plasma confinement in fusion energy, quantum decoherence in quantum computing, and gravitational singularities in astrophysics through the lens of higher-dimensional weaving.
Higher-dimensional embeddings like in the Randall–Sundrum model provide solutions to interpreting black holes and wormholes as folds in higher-dimensional weaves, showcasing how singularities may be a projection of a smooth higher-dimensional geometry.
The Woven Continuum Theory emphasizes a philosophical viewpoint that singularities are not true endpoints but rather opportunities for evolution through higher-dimensional corrections, reflecting interconnected patterns in the universe.
Concrete next steps outlined include explicit constructions, toy simulations, and experimental or computational tests to further validate and explore the implications of the theory in various fields.
A Numpy proof example illustrates how the theory operates in a toy model scenario, showing how a 4D-inspired correction can eliminate zeros in a 3D field by borrowing from a quaternionic basis.
The article delves into the Network of Hairy Balls, illustrating how multiple singularities can be addressed in a larger dimensional framework, presenting a metaphor of interconnected 'hairy balls' in a multi-dimensional weave.
The Woven Continuum Theory not only introduces mathematical and physical concepts but also carries philosophical principles that view limits as illusions, advocate balance through recursion, and highlight the interconnected nature of complex systems in the universe.

Read Full Article

15 Likes

Dev

123

Image Credit: Dev

Node.js Image Upload System: File Handling, Storage, and Database Integration

This tutorial focuses on building a server-side image upload system using Node.js.
The system involves handling image uploads, storing them, managing metadata, and serving them back to the application.
Steps include configuring routes, controllers, and using Multer for multipart/form-data handling.
Setting up file storage, integrating with a database, and creating endpoints to manage image data are key components.
Code snippets demonstrate creating routes for image upload and deletion functionality.
Functionality for uploading, removing images, and sending images from the frontend are explained.
Handling main images, additional images, and updating post data are detailed.
Considerations such as image optimization, AWS S3 integration, and security measures are mentioned for future enhancements.
The tutorial emphasizes error handling, security, file size limits, and encourages contributions and feedback.
The provided code repository contains the complete tutorial implementation for reference.

Read Full Article

7 Likes

Javarevisited

322

Image Credit: Javarevisited

Top 23 Design Patterns Experienced Java Programmers Should Learn

Design Patterns are a tried and tested way of solving problems within a specific context, providing solutions discovered by the wider community.
Learning Design Patterns can help in writing better code by utilizing established solutions to common object-oriented development tasks.
There are 23 common object-oriented design patterns that experienced Java programmers should learn to enhance their coding skills.
These patterns offer reliable solutions that may require some customization but generally provide effective problem-solving methods when applied correctly.

Read Full Article

19 Likes

Dev

172

Image Credit: Dev

Dumping Credentials with Python: Automating LSASS Access and Credential Extraction Post-Exploitation

Accessing LSASS in post-exploitation scenarios provides valuable data such as passwords, hashes, and credentials, making it a prime target for red teamers and attackers.
Extracting data from LSASS with Python offers a powerful tool for red teamers, giving insight into detection and defense measures that might obstruct such attempts.
LSASS plays a crucial role in storing authentication artifacts, enabling attackers with the right access to perform pass-the-hash or pass-the-ticket attacks.
Microsoft has hardened LSASS against unauthorized access through measures like running it as a Protected Process Light and utilizing Virtual Secure Mode.
Python-based approaches for LSASS dumping include direct memory access using ctypes and Windows APIs, minidump creation with MiniDumpWriteDump, and parsing dumps with pypykatz.
Evasion techniques to stay stealthy during credential dumping involve using legitimate processes, forking LSASS, and avoiding disk I/O to prevent detection.
Python's flexibility allows red teamers to automate LSASS credential extraction quietly and efficiently, navigating the evolving landscape of detection by defenders.
Understanding the mechanisms of LSASS credential extraction and employing evasive workflows are essential for red teamers to maintain their capabilities effectively.
Automating LSASS credential dumping using Python provides red teamers with a potent capability when executed with precision and stealth.
LSASS access and credential extraction offer red teamers key insights into Windows systems, enabling them to navigate networks effectively and escalate privileges.
For further information and updates, follow DevUnionX at https://x.com/DevUnionX.

Read Full Article

10 Likes

Javarevisited

185

Image Credit: Javarevisited

How Long does It take To Learn Linux?

Learning Linux can be a quick process, with the basics being graspable in a weekend. However, mastering Linux may take weeks as there are numerous commands and concepts to understand.
The time it takes to learn Linux depends on your specific goal. For developers, it might take a week, while for System Administrators, it could be months due to the requirement of deeper knowledge.

Read Full Article

11 Likes

Medium

Image Credit: Medium

The Silent Threat: Unhandled Promise Rejections in JavaScript

Unhandled promise rejections in JavaScript can lead to silent failures, missing data, broken features, or security holes.
Unlike synchronous errors, unhandled promise rejections happen asynchronously, may not crash your script, and are not always immediately visible.
Adding a `.catch()` handler after a promise rejection does not retroactively fix the issue; it needs to be handled immediately.
To prevent silent failures, it is crucial to attach a `.catch()` to every promise in JavaScript or use `try/catch` with `async/await`.

Read Full Article

Medium

379

Image Credit: Medium

Quaternions: Creating a Class Using Dunder Methods in Python

Quaternions are an extension of complex numbers and are useful in computer graphics for transformations.
Creating a custom Quaternion class in Python involves implementing dunder methods for various operations.
The __init__ method initializes Quaternion variables, checking for valid input types like ints and floats.
The __str__ method converts Quaternions into readable strings using list concatenation.
__repr__ method represents Quaternions for easily replicating objects with eval function.
Arithmetic operations like addition, subtraction, multiplication, and division are implemented using dunder methods.
Handling different data types like complex numbers, ints, and floats in arithmetic operations requires type checks.
Additional methods for right hand operations, in-place operators, and comparison operators are implemented.
Class methods are utilized for static functions like converting to/from ints and floats and creating identity Quaternions.
Dunder methods simplify development by leveraging built-in operators, reducing additional methods needed for custom classes.

Read Full Article

22 Likes

Logrocket

344

Image Credit: Logrocket

It’s time to break the cycle of developer elitism

Software development is a fast-paced field where staying relevant can be challenging, leading to elitism issues within the community.
Elitism in software development hampers communication, humility, and over-reliance on AI, creating barriers for newcomers.
The author highlights the negative impact of elitism on communication and the need for a more inclusive approach in the industry.
Everyone has a unique journey in software development, and elitism often undermines the diverse paths individuals take.
Platforms like Stack Overflow, while valuable, can sometimes hinder new developers due to high-quality standards and potential elitism.
The article discusses the limitations of AI in addressing the hostility faced by novice developers and the risks of receiving inaccurate information.
Personal anecdotes emphasize the importance of humility in mentorship and fostering a supportive environment for junior developers.
Breaking the cycle of elitism is crucial for the growth and sustainability of the developer community, encouraging mentorship and inclusivity.
Developers are urged to combat elitism, enhance communication skills, and be approachable to mentor and support the next generation.
The article concludes that fostering inclusivity and mentorship in the developer community is essential for its continued success and growth.

Read Full Article

20 Likes

Medium

203

Image Credit: Medium

What Is Considered A Large Amount Of Bitcoin?

Defining a large amount of Bitcoin can vary depending on individual wealth, location, and background.
Many consider a large amount of BTC to be valued at $10,000 or more, with some saying anything above $100,000.
It's recommended that Bitcoin comprises 5% to 20% of your entire investment capital, with 5% being safe and 20% considered risky.
Buying large amounts of Bitcoins can be done through exchanges and OTC broker platforms, but it's essential to be prepared and start with smaller investments if you're inexperienced.

Read Full Article

12 Likes

Johndcook

393

Iterated logarithm

Logarithms provide a way to express large numbers compactly, and iterated logarithm involves taking the log multiple times until the result is less than or equal to 1.
The iterated logarithm is denoted as log*b(x), indicating the number of times you need to take the logarithm base b to reach a value less than or equal to 1.
Implementing the iterated logarithm in Python involves a simple function that iterates the logarithm until the desired condition is met.
Skewes' bounds and Mersenne primes are examples where iterated logarithms are used to determine the number of iterations required to reach a small value.

Read Full Article

23 Likes

Medium

326

Image Credit: Medium

Why Writing Python Feels Like Writing Poetry

Writing Python feels like writing poetry due to its focus on readability, clarity, and simplicity.
Python is designed to prioritize clarity and simplicity, a philosophy established by Guido van Rossum.
The Python community upholds the value of readability and simplicity, evident in the Zen of Python guiding aphorisms.
Python's language design emphasizes clarity, where form emerges from meaning and every word has significance.

Read Full Article

19 Likes

PlanetPython

238

Image Credit: PlanetPython

Django Weblog: Django security releases issued: 5.2.2, 5.1.10, and 4.2.22

Django team has issued security releases for Django 5.2.2, 5.1.10, and 4.2.22.
Security issue CVE-2025-48432 addressed potential log injection via unescaped request path.
Severity of the issue is 'moderate' as per Django's security policy.
Users are advised to upgrade Django versions to address the security vulnerabilities.

Read Full Article

14 Likes

Dev

950

Image Credit: Dev

Reportgen.io vs Html2pdf.app - Which PDF API Should You Use in 2025? ⚔️

Reportgen.io is designed for dynamic PDF generation with multiple templating engines, pay-per-use pricing, and a developer-centric dashboard.
Html2pdf.app is a lightweight, credit-based service for straightforward raw-HTML-to-PDF jobs.
Reportgen.io supports templating engines like EJS, Handlebars, GoTempl, or raw HTML, while Html2pdf.app only supports raw HTML.
Reportgen.io is more suitable for highly-customized, data-driven documents, while Html2pdf.app is better for turning single pages into PDFs on a tight budget.

Read Full Article

11 Likes

Medium

5.5k

Image Credit: Medium

Understanding Vapor Framework for iOS Developers: A Simple Breakdown of Project Structure

Setting up Vapor framework involves checking Swift version, installing Homebrew and Vapor Toolbox.
Vapor projects use controllers to handle specific requests and perform actions like data manipulation.
Migrations in Vapor are like architectural blueprints defining database structure, allowing changes like adding new fields.
Models in Vapor represent real-world items, corresponding to database tables and holding specific information.

Read Full Article

12 Likes

For uninterrupted reading, download the app

Programming News

Discover more