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New 47 GitHub Repositories - OpenSource of Dec 20, 2024

Tads Basic Game Objects, Lightweight JavaScript Library
Dynamic Pydantic – Create Pydantic Models Using AI
Reverse Engineering – Lesson 1: x86 Course (Part 1: Goals)
A Raycaster in Bash
Low-Level Guidance Parser
Dockside: Self-Hosted GitHub Codespaces
Wa-automate-Node.js: Node.js library for a high-level API to control WhatsApp
Instruct LLMs to do what you want in Ruby
Want a faster MySQL drop-in replacement? Try MemCP
Video Seal: Open and Efficient Video Watermarking
Model Validation Using LLMs

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Dev

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Enhancing LRU Cache with Configurable Data Persistence

In this article, we explore how to extend an in-memory cache with configurable data persistence.
The goal is to design a flexible and scalable caching system that decouples storage mechanisms from the caching logic.
The article leverages the Adapter and Strategy patterns to create an extensible system that allows seamless integration of databases or services as needed.
A shared API abstraction, akin to ORM systems, ensures storage such as localStorage, IndexedDB, or even a remote database can work interchangeably with minimal code changes.
The cache is agnostic of storage details, and there is a flexible runtime selection of storage backend using the Strategy pattern.
Additionally, the article demonstrates best practices for singleton cache, async initialization, and lazy loading.
This design is robust and is available in the form of an npm package—adev-lru.
The article provides scope for further enhancements, such as optimizing sync logic for better performance.
The full source code for the adev-lru repository is available on GitHub.
The author welcomes contributions to make this caching system even better.

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Medium

Programming: The Heart of Modern Innovation.

Programming began in the 19th century with Ada Lovelace and has continued to evolve from assembly languages to high-level frameworks.
Programming is essential in various sectors like healthcare, finance, entertainment, shopping, education, and transportation.
Learning programming opens up job opportunities and cultivates problem solving, logical thinking, and creativity.
Programming is the foundation for future innovations such as artificial intelligence and space exploration, shaping tomorrow's possibilities.

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Medium

SIESTALTSIC TO ARISTO

A group of people visited the zoo in Aburar and enjoyed seeing various animals and birds.
They witnessed birds chirping and floating waterfowls in the clear water.
They also encountered jackals, foxes, and rode an elephant with fear.
The visit to the zoo was described as very enjoyable.

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Dev

245

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AI Models Can Now Critique Their Own Work, Boosting Performance by 13%

Study explores using AI-generated self-critiques to improve language model training
Introduces novel method where models evaluate and critique their own outputs
Demonstrates 13% improvement in reward modeling accuracy
Shows scalability and effectiveness for both small and large language models

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Dev

401

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5 Frontend Development Myths That Need to Die in 2024

Frontend development has come a long way in the last decade, but there are persistent myths that need to be debunked.
Myth 1: CSS Is Easy! - CSS may seem simple on the surface, but it is a powerful tool with complexities like specificity wars and browser inconsistencies.
Myth 2: Frameworks Solve Everything - While frameworks like React and Angular are useful, they may not be necessary for small, static sites.
Myth 3: The Backend Is the Hard Part - Frontend development involves solving complex problems like state management and ensuring accessibility.
Myth 4: You Can Skip Accessibility If You’re in a Rush - Accessibility is not optional and should be considered a non-negotiable part of the workflow.
Myth 5: Frontend Development Will Be Fully Automated Soon - While AI tools can assist with repetitive tasks, building intuitive interfaces requires human creativity and problem-solving.
Let’s challenge these myths and celebrate the complexity and creativity of frontend development.

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Dev

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Language Models Boost Robot Learning with Limited Training Data

LaMo is a new framework that combines language models with offline reinforcement learning.
It uses pre-trained language models to improve motion control with limited data.
LaMo features four key components: sequential pre-training, LoRA fine-tuning, MLP transformation, and language prediction loss.
It performs well in sparse-reward tasks and matches the performance of value-based methods, particularly with small datasets.

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Dev

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Winter Solstice: Frontend Challenge - December Edition

For the Frontend Challenge - December Edition, Glam Up My Markup: Winter Solstice, the developer created a visually dynamic and informative landing page dedicated to the celebrations of the Winter Solstice around the world. The page features a snowfall animation, gradient texts and buttons, responsive design, and various content sections covering the science, cultural traditions, and global celebrations of the solstice.
The developer incorporated a wintry atmosphere using a linear gradient background and a snow animation that flows gently throughout the page. The header and navigation are clean and visually appealing with gradient text and hover effects.
The snowfall background animation using CSS keyframes adds a touch of liveliness to the page. The developer learned more about CSS keyframes and background animations while working on this challenge.
The primary challenge was integrating the snowfall animation smoothly without affecting the page's loading speed. The developer optimized the background images and animations to ensure a smooth user experience.

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Dev

392

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Web Workers for Multithreading in JavaScript

Web Workers are a feature of the Web API that allows JavaScript code to run in the background on a separate thread, improving performance by offloading resource-intensive tasks from the main thread.
Web Workers operate in a different execution context and can communicate with the main thread via messages. They do not have access to the DOM, window, or document objects.
To use Web Workers, create a separate JavaScript file containing the code to be executed in the background. Initialize the worker in the main thread, send and receive data through messages, and terminate the worker when no longer needed.
Web Workers offer improved performance, better user experience, and scalability by preventing the main thread from being blocked, allowing the UI to remain responsive even during intensive operations.

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Medium

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Starting the YouTube Channel This is a YouTube channel I started 5 months ago.

A YouTube channel was started 5 months ago.
Inspired by the success of Zach D Films, who has 14 million subscribers and billions of views per month.
The decision to start the channel was made due to low competition and as a case study.
A third person named Woo was brought in to help with the channel.

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Prodevelopertutorial

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Tree data structure tutorial 14. Fenwick trees and implementation

Fenwick tree is an efficient data structure for range sum queries and range updates which takes advantage of the fact that all numbers can be represented by 2^n.
We can calculate the range in power of 2.
The Fenwick tree algorithm pre-computes and stores sums for specified ranges such as [0, r], where r is a power of two or less.
It requires less space than the segment tree and takes O(n log n) time to build, O(log n) time for updates, and O(log n) time to compute the range sum.
We can use Fenwick tree to compute the sum for the range [ 0 – 3].
We can update the array elements by starting from the index and then moving rightwards to update the next ranges.
We can achieve this by binary representation i.e., go to the index and add the last set bit to know the next index to be updated.
The article explains the concept of Fenwick tree with a step-by-step explanation on how to implement range sum and range update queries and shows a C code implementation.
Fenwick tree is a useful and efficient data structure that can be applied in many algorithmic problems involving range queries and update operations.
It is faster than simple brute force approach as well as the Segment Tree data structure.

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Prodevelopertutorial

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Tree data structure tutorial 13. Lazy propagation of segment trees with example

Lazy propagation is a technique used in segment trees to optimize updates on a large amount of data.
It reduces the number of unnecessary updates by postponing them until necessary.
The need for lazy propagation arises when there are frequent update queries on the segment tree.
Lazy propagation helps improve performance by updating values only when required.

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Prodevelopertutorial

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Tree data structure tutorial 12: Performing minimum Range query in Segment Tree and implementation

In this chapter we shall learn about below topics:
Partial Overlap
Total overlap
No overlap
Construct Segment Tree
Implementation of Min Range Query Segment Tree in Cpp
Performance of range queries is the major focus of this chapter.
We have 3 different methods to perform range queries.
Partial overlap and total overlap methods have been explained with examples.
We also look at how to construct a segment tree.

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Dev

205

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CustomText - Custom Widget Series

This article is part of the Custom Widget Series, providing tips and code for creating reusable and advanced Flutter widgets.
The article introduces the CustomText widget, which simplifies the process of styling Text widgets in Flutter.
The CustomText widget allows for easy customization of properties such as color, font size, font weight, and max lines.
The article also highlights the use of style factories and the rich() factory for creating complex text widgets, as well as the ability to make certain parts of the text clickable.

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Dev

303

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The Easiest Way to Package Your Python Files(Turn to .exe Files)

Python does not produce executable files during compilation, but a program can automate the packaging process using the pyinstaller library.
To use the automated packaging tool, the prerequisite step is to install conda for creating and managing virtual environments.
The tool supports packaging in Windows environments specifically for creating .exe files.
The GitHub Repository provides two tools: EasyPackager and PeasyPackager, where EasyPackager is recommended for simpler packaging needs.

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