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Next JS vs React Performance: A Comprehensive Comparison

Next JS and React are major frameworks used in Web development.
Next JS is built on top of React and provides additional features like server-side rendering (SSR) and static site generation (SSG) with built-in support for TypeScript.
React excels in building interactive UIs with its component-based architecture and virtual DOM.
Performance optimization in modern web development is crucial for providing a positive user experience, quick response and high SEO rankings.
Next JS wins over React in terms of page loading and speed optimization due to its SSR and SSG techniques.
React leverages client-side rendering (CSR) to handle heavy DOM updates efficiently. However, its SEO optimization, load times, and rendering capabilities can be improved with SSR, SSG, and other optimization techniques.
Next JS provides automatic code splitting, optimized image handling, and built-in performance optimization tools that handle the complexities of optimization.
React uses component reconciliation and memoization, and offers several techniques for speed optimization like lazy loading, pure components etc.
Next JS is beneficial for static content-heavy, SEO-driven applications, while React is ideal for dynamic, client-side applications.
Next JS effectively handles dynamic content with incremental static regeneration and automatic code splitting, ensuring performance is not compromised.

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Medium

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Keyboard Shortcuts(Everyone Should Know)

Ctrl/command + Home: Go to the beginning of a document or webpage.
Ctrl/command + End: Go to the end of a document or webpage.
Ctrl/command + Left/Right Arrow: Move cursor one word left/right.
Ctrl/command + Up/Down Arrow: Move cursor one paragraph up/down.
Alt + Tab: Switch between open windows.

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Dev

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What Does setTimeout(..., 0ms) Really Mean in JavaScript? (Event Loop Explained!)

setTimeout(..., 0ms) in JavaScript does not run immediately, but is deferred to the event loop.
JavaScript's event loop handles tasks in a specific order: main tasks, microtasks, then timers.
The code example with setTimeout(() => { ... }, 0) demonstrates this order of execution.
Understanding how 0ms works helps in writing better asynchronous code and explains JavaScript delays.

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Dev

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Learn Redux Toolkit - React (TypeScript)

Redux is a state management library used in React applications, and Redux Toolkit is its official library for managing global state in a simpler and structured way.
Redux Toolkit simplifies Redux setup by providing features like configureStore(), createSlice(), and createAsyncThunk().
The basic steps to set up Redux Toolkit in a React project include setting up the store, integrating it into the app, creating slices, and using Redux in components.
Redux Persist is a library used to save application state to local storage, and it can be implemented with Redux Toolkit using the redux-persist library.

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Dev

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10 Shocking React and Node.js Tips That Will Change the Way You Code Forever!

Lazy loading components can improve initial load time and user experience.
React.memo can prevent unnecessary renders and boost performance.
For small to medium apps, React's useReducer and useContext can manage state seamlessly.
CSS-in-JS libraries like styled-components or emotion can help with scoped styling.

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Medium

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Underdogs of Programming Languages That Few Dare to Try

Crystal, Elixir, and Haxe are the underdogs of programming languages.
Crystal offers Ruby's syntax and the speed and efficiency of a compiled language.
Elixir is built for distributed systems and offers fault tolerance and high concurrency.
Haxe allows writing code once and compiling it into multiple languages for cross-platform development.

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Medium

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Title: 5 Powerful ChatGPT Prompts to Streamline Your Workflow and Reclaim 4+ Hours Every Day

ChatGPT is a powerful AI assistant that can help optimize daily routines and lighten your workload.
Five carefully designed ChatGPT prompts are introduced to save more than four hours per day.
The Daily Briefing and Prioritization Prompt helps start the day fully informed and ready to tackle important tasks.
This prompt automates sorting through news and emails, providing a summary of top industry news.

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Dev

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Converting Recursion to Iteration Using a Stack: A Practical Guide

Recursion is a powerful technique in computer science, often used for tasks like tree traversal, depth-first search, and backtracking algorithms. However, recursion can be less efficient in terms of both time and space due to the overhead of function calls and maintaining the call stack. In some cases, it’s beneficial to convert recursion to an iterative approach using an explicit stack to simulate the recursive calls.
There are several reasons why you might want to convert recursion to iteration:
When converting a recursive function to an iterative one using a stack, the general approach remains similar across different types of algorithms (like tree traversals, backtracking problems, or graph traversal). Below is a flexible template that can be adapted to various scenarios.
The stack should be initialized with the starting state, which could be the initial arguments or the first node in a traversal.
In recursion, the base condition checks if further recursion is necessary. In the iterative approach, you can perform the same check inside the loop. You may use continue to skip further processing when the base condition is met.
Process the state of the current iteration (equivalent to the processing that would occur at the current recursive call).
This iterative version uses the stack to store the current state of the permutation. The backtracking is handled by pushing and popping the states from the stack.
Converting recursion to iteration using a stack is a valuable technique for many algorithms, especially those involving backtracking or tree/graph traversal. By using an explicit stack, we can avoid deep recursion, manage function states manually, and ensure that we have better control over the algorithm’s execution. These examples should serve as a guide to help you tackle similar problems in your own code.

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PlanetPython

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Kushal Das: Open Source talk at KTH computer science students organization

Kushal Das gave a talk on Open Source and career at KTH computer science students' organization.
He emphasized that contribution size does not matter, but continued contribution can positively impact one's life and career.
He discussed the history of the Free Software movement, Open Source, and recommended watching the documentary 'The Internet's Own Boy.'
Some participants were surprised to hear about Sunet's Open Source work, and one student even contributed a small patch to a project.

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Dev

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15 System Design Resources for Interviews (including Cheat Sheets)

System design interviews have become an integral part of the hiring process for many tech companies, especially for senior and architect roles
Preparing for these interviews can be challenging due to their broad scope and complexity but good resources can help you master system design concepts and excel in your interviews
Here are the 15 best resources to prepare for system design interviews in 2025, categorized into websites, online courses, books, blogs, and newsletters
ByteByteGo is a popular System design resource particularly known for its visual approach to explaining system design concepts
Codemia.io offers more than 120+ system design problems with AI assistance and feedback when you submit your solution
DesignGurus.io offers Grokking the System Design Interview and Grokking the Advanced System Design interview courses
Exponent offers mock interviews, video lessons, and detailed guides on various system design topics. Their courses are created by industry professionals with experience at top tech companies.
Udemy offers numerous courses on system design, with practical examples and real-world scenarios. Their courses are affordable and flexible.
Educative.io offers a range of system design courses that are ideal for those who prefer reading over watching videos. They also have AI-powered courses.
System Design Interview --- An Insider's Guide by Alex Xu is a must-read book for anyone preparing for system design interviews.

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Dev

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Unlocking the Power of OOP in Java: A Beginner’s Guide

OOP (Object-Oriented Programming) is a way of writing programs where everything revolves around objects.
OOP makes programs modular, reusable, and easier to understand.
Key concepts in OOP for Java include class, object, packages, and four main principles.
Learning OOP unlocks superpowers in programming, enabling the building of apps and solving complex problems effectively.

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Dev

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Part 9: Building Your Own AI - Natural Language Processing (NLP) for Language Understanding

Natural Language Processing (NLP) is a field of AI that enables machines to understand and generate human language.
Key components of NLP include text preprocessing, word embeddings, and sequence models.
Common NLP tasks include text classification, machine translation, text summarization, and named entity recognition.
NLP trends and tools include transformers, pre-trained models, and real-time applications like voice assistants and chatbots.

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Medium

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The digital reality

In the mid-20th century, pioneers like John von Neumann and Alan Turing laid the foundation for computer science, emphasizing intelligence and collaboration.
The rise of the internet in the 1980s and 1990s connected early users and offered open access to information.
Companies like Facebook and Twitter capitalized on the internet's openness but compromised its promise by centralizing power and exploiting user data.
We now live in a digital reality where the line between digital and physical worlds is blurred, and the question of freedom in the digital age arises.

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Medium

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Artificial Intelligence: Revolution or Chaos?

AI offers unmatched efficiency in healthcare, enabling faster and more accurate diagnoses.
Intelligent robots optimize production lines, increasing productivity and reducing costs.
AI-powered virtual assistants and educational platforms democratize access to knowledge.
However, concerns include job loss, bias and discrimination, and technological dependence.

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Dev

405

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The Role of Algorithms in Modern Computational Systems

Algorithms are the foundation of computational systems and software design.
They are used to solve problems and have applications in areas such as cryptography, artificial intelligence, and distributed systems.
Algorithms can be designed using paradigms like divide and conquer, dynamic programming, and greedy algorithms.
Optimization techniques, including algorithmic and hardware-specific optimizations, improve efficiency.

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