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

A naukri.com initiative

New

Home

Programming News

Dev

235

Image Credit: Dev

npm vs npx, which one is better?

npm and npx serve different purposes in JavaScript development, with npm focusing on package installation and management, while npx is about running packages without global installation.
npm, short for Node Package Manager, is used for managing packages and libraries in projects, with a wide range of powerful packages available on npmjs website.
In contrast, npx, a tool that came with npm v5.2.0, allows running commands from packages without the need for global installation in the system.
Using npm, packages are added to the node_modules folder and recorded in the package.json file, while npx is more focused on running commands as-needed without cluttering the system.
npx simplifies running specific package versions on the fly, avoiding the need for manual upgrades or downgrades compared to globally installed packages.
npm is suitable for managing project dependencies and global installations, whereas npx is preferred for running CLI commands without global installation and for specifying package versions.
Understanding the differences between npm vs npx is crucial for efficient JavaScript development and project management.
Ultimately, the choice between npm and npx depends on the specific workflow needs of the developer, with both tools offering unique advantages for different scenarios.
npx was created to improve user-friendliness by avoiding unnecessary global installations, enabling running specific package versions, and simplifying the execution of command-line tools.
Both npm and npx play important roles in modern JavaScript development, with npm handling package management and npx facilitating efficient command execution without global clutter.

Read Full Article

14 Likes

Dev

375

Image Credit: Dev

Getting started with local AI development using Docker Model Runner

Docker Model Runner is a tool designed to make running Large Language Models (LLMs) locally easier.
It runs LLMs directly on the local machine and uses Docker to wrap a convenient API interface around it.
Model Runner is currently in beta and works only on Docker Desktop for Mac with Apple Silicon.
It is useful for prototyping AI features, keeping data private, learning and experimenting with LLMs, and building offline-ready apps.

Read Full Article

22 Likes

Medium

347

Image Credit: Medium

Brute Force Algorithm: The Old School Powerhouse of Problem Solving

Brute force algorithm systematically explores every possible solution without optimization.
It generates all possible options, tests every option, and stops when the correct one is found.
While brute force guarantees a solution, it can be slow for problems with a large solution space.
Brute force is a common starting point for programmers to understand problem structures before optimization.

Read Full Article

20 Likes

Medium

Image Credit: Medium

5 Hot-Takes for Data Engineers

Don't prioritize collecting badges and certificates over practical skills and experience.
Stay updated with the changing data ecosystem and understand underlying trends.
Focus on clear communication and the ability to explain solutions to non-technical stakeholders.
Invest in documentation and naming conventions for efficient collaboration.

Read Full Article

3 Likes

Dev

331

Image Credit: Dev

Unlocking the V8 Engine: Why Your JavaScript is Faster Than You Think

V8, Google’s high-performance JavaScript engine, powers browsers like Chrome and backend runtimes like Node.js.
V8 has four core components: Parser, Ignition (Interpreter), TurboFan (Optimizing Compiler), and Garbage Collector.
The execution pipeline in V8 involves parsing code into AST, compiling it into bytecode, optimizing it with TurboFan, and deoptimizing if assumptions fail.
V8 uses JIT compilation, speculation and assumptions, profiling-guided optimization, and on-stack replacement to improve performance.

Read Full Article

19 Likes

Dev

Image Credit: Dev

Unpacking the MCP Base Protocol

The Model Context Protocol (MCP) base protocol, rooted in JSON-RPC 2.0, is crucial for reliable client-server communication in apps.
The base protocol, as of the latest spec, offers modularity, allowing optional features to be added based on app requirements.
It emphasizes separation of concerns, handling core messaging while enabling additional functionalities to be integrated as needed.
Core message types within the MCP include requests, responses, and notifications, each following JSON-RPC 2.0 guidelines.
Requests initiate actions, responses deliver results or errors, and notifications provide one-way updates.
Batching messages for efficiency and defining transports like stdio and Streamable HTTP are key aspects of the MCP base protocol.
Lifecycle management ensures proper initialization, operation, and shutdown of MCP connections.
Authorization features, including OAuth 2.1 support, provide security options for locking down MCP interactions.
The MCP base protocol's TypeScript schema serves as a precise reference, ensuring implementation alignment with the specification.
Developer-friendly and lightweight, the MCP base protocol offers flexibility and modularity, making it an attractive choice for various projects.

Read Full Article

5 Likes

Dev

116

Image Credit: Dev

How I got 3 offers in 1 month

The author shares their experience of getting 3 job offers in 1 month in the tech industry.
They recommend keeping the resume simple and using a Chrome extension to customize it for every application.
The author advises applying to 50 jobs a day on LinkedIn, tailored with the extension mentioned.
They also suggest using InterviewCoder or similar platforms to help with knowledge gaps during the interview stage.

Read Full Article

6 Likes

Amazon

295

Image Credit: Amazon

Converting embedded SQL in Java applications with Amazon Q Developer

Migrating from Oracle to open source databases like PostgreSQL often involves converting embedded SQL in Java apps, a time-consuming and error-prone task.
AWS offers a solution using Amazon Q Developer and AWS DMS, automating SQL conversion in Java apps for database migration.
Amazon Q Developer, powered by AI, identifies and converts SQL statements from Oracle to PostgreSQL dialects, reducing manual effort.
This automation speeds up the process significantly, minimizes errors, and allows developers to focus on higher-value tasks.
When combined with AWS DMS for schema conversion and data replication, this automated solution streamlines the entire migration workflow.
The solution ensures consistency across the codebase, simplifies technical aspects of migration, and aligns with organizational efficiency goals.
The conversion process is exemplified by transforming Oracle-specific SQL queries from Java classes to PostgreSQL-compatible queries.
The end-to-end testing after conversion involves updating database connection settings, executing test suites, and monitoring for errors.
The approach of automated SQL conversion with Amazon Q Developer offers reduced migration time, improved accuracy, cost savings, and seamless integration.
Authors like Suruchi Saxena, Jason Varghese, and Venugopalan Vasudevan contribute expertise in Generative AI, DevOps, cloud migrations, and solutions architecture.
The collaboration of AI-driven tools like Amazon Q Developer with AWS services enhances database migration efficiency and accuracy.

Read Full Article

17 Likes

Javacodegeeks

Image Credit: Javacodegeeks

Chaos Engineering for Java: Testing Spring Boot Resilience with Gremlin & Litmus

Chaos Engineering helps to identify weak points before users do, validate redundancy mechanisms, and improve observability.
Gremlin provides a SaaS platform to inject failures via API or UI, allowing for controlled chaos experiments.
Litmus is an open-source chaos framework that integrates with Kubernetes, enabling fine-grained control over chaos experiments.
Implementing defensive coding practices, such as retries, circuit breakers, and chaos-aware health checks, can improve the resilience of Spring Boot applications.

Read Full Article

4 Likes

Logrocket

Image Credit: Logrocket

How to add custom fonts in React Native

Using custom fonts can provide apps with a unique identity, and in React Native, this guide explores adding custom fonts, including Google Fonts integration.
For React Native CLI projects, steps include creating an assets/fonts folder, adding font files, creating react-native.config.js to specify font assets path, and using fontFamily in styles.
For Expo projects, installation of required packages like expo-font is needed, or for Google Fonts, use @expo-google-fonts/[font-name], then utilize useFonts Hook to load fonts.
The article covers integrating Google Fonts like Quicksand and Raleway, downloading font files, creating assets/fonts folder, and linking fonts for React Native CLI projects.
In Expo projects, custom fonts are demonstrated using the useFonts Hook, Google Fonts installation, and integrating custom Google Fonts in the project.
Best practices for React Native fonts are explained, including using system fonts, dynamic font loading, adapting to accessibility preferences, and validating font rendering across devices.
Common pitfalls when working with custom fonts are discussed, such as font loading time, font family names consistency, font path errors, performance impact, and font weight/style issues.
Issues with production builds and assets linking errors like react-native-asset problems are outlined, and recommendations for resolving them are provided.
Integrating custom fonts in React Native enhances user experience strategically, and following best practices ensures optimal performance in applications.
Key takeaways include using the useFonts Hook for Expo projects, react-native.config.js and npx react-native-asset for React Native CLI projects, handling font loading states, considering system fonts, and managing font file sizes.
By implementing these practices, custom fonts can be seamlessly integrated into React Native apps, improving user experience and performance.

Read Full Article

5 Likes

Dev

371

Image Credit: Dev

Open Source is Soil: The Greening Philosophy

Open source is soil. It’s not just where we build — it’s where things grow.
Greening is an opinionated, full-stack project automation tool for solo developers and creative coders.
Greening exists to make the early stage of software development effortless, removing friction from the planting process.
The open-source ecosystem is a living commons, and Greening provides a substrate for creative, scalable, and repeatable growth.

Read Full Article

22 Likes

Dev

Image Credit: Dev

How to Generate a GitHub Token for Pushing Repos with Greening

When using greening new to auto-create and push a repo to GitHub, you'll need a GitHub token with proper permissions.
Here’s how to generate one and use it securely:
Step 1: Generate a New Token
Step 2: Add It to Your Environment

Read Full Article

6 Likes

Medium

135

Image Credit: Medium

My Weird Journey Creating a Community Centered Around Curating News Sources

The author recounts their experience of creating a website centered around curating news sources.
They initially started building the website using a template from Vite.
After facing issues with their backend choice, they migrated to Supabase.
The author launched the website, called AnythingFeed, in about a week, with a focus on shipping fast and not worrying about code quality.

Read Full Article

8 Likes

Medium

263

Image Credit: Medium

Best React Component Libraries in 2025 (And How to Use Them)

React component libraries in 2025 provide a solution for building complex features without starting from scratch.
Using a component library saves time and enhances productivity.
ShadCN/ui is a headless UI kit built on top of Radix, offering beautiful and customizable components.
The library allows flexibility in design decisions and ensures fast and functional components.

Read Full Article

15 Likes

Medium

208

Image Credit: Medium

Expert Digital Marketing Suggestions for Business Growth in 2025

AI will continue to play a significant role in enhancing marketing strategies, offering automation, optimization, and insights.
Video marketing will dominate social media platforms, websites, and email campaigns, increasing brand awareness and driving conversions.
Personalization through AI and data analytics will drive customer loyalty and brand advocacy.
Optimizing for voice search and embracing social commerce will be crucial for businesses to stay competitive.

Read Full Article

12 Likes

For uninterrupted reading, download the app

Programming News

Discover more