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حقن التبعيات ليس مجرد تقنية، بل هو نمط يُسهم في بناء أنظمة نظيفة، قابلة للتوسّع، وسهلة الصيانة. اعتماد هذا الأسلوب يرفع من جودة العمل، ويمنح المطور قدرة أكبر على التحكم في هيكلة التطبيق، خاصةً في الأنظمة الكبيرة أو المعتمدة على خدمات متعددة.

إذا كنت تعمل على تطبيق معقّد أو تستخدم إطاراً حديثاً، فإن تطبيق حقن التبعيات يعد خطوة أساسية لبناء بنية متينة ومرنة.

Add these lines:

ClientAliveInterval 60
ClientAliveCountMax 3

When building a multilingual React application, translating the visible content is just part of the job. To make your app SEO-friendly and user-centric, you also need to:

• Translate URLs/slugs (e.g., /about-us → /fr/a-propos)
• Maintain SEO with hreflang for each language
• Improve UX by aligning URLs with user language
• Ensure route accessibility via browser language or manual switching

In 2025, React globalization goes beyond just i18n (internationalization). It includes:

• Text translation (i18n)
• Locale-aware formatting (dates, numbers, currencies)
• Cultural UX adaptations (e.g., RTL layouts, color symbolism)
• Language switching + SEO compatibility
• Region-based content rendering (e.g., laws, units, timezones)

With i18next and react-i18next, you can:

• Translate your app without performance loss
• Format dates, numbers, currencies natively
• Scale your translations across large React apps

Create a webpack.config.js:

const HtmlWebpackPlugin = require('html-webpack-plugin');
const ModuleFederationPlugin = require('webpack').container.ModuleFederationPlugin;
const path = require('path');

module.exports = {
  mode: 'development',
  devServer: {
    port: 8081,
  },
  entry: './src/main.js',
  output: {
    publicPath: 'http://localhost:8081/',
  },
  plugins: [
    new ModuleFederationPlugin({
      name: 'analytics_app',
      filename: 'remoteEntry.js',
      exposes: {
        './Analytics': './src/components/Analytics.vue',
      },
      shared: require('./package.json').dependencies,
    }),
    new HtmlWebpackPlugin({ template: './public/index.html' }),
  ],
};

import create from 'zustand';
import { persist } from 'zustand/middleware';

const useStore = create(persist(
  (set) => ({
    count: 0,
    increase: () => set((state) => ({ count: state.count + 1 })),
  }),
  {
    name: 'counter-storage',
  }
));

Zustand allows you to select specific parts of the state to prevent unnecessary re-renders:

import React, { useState, useCallback } from 'react';

function Counter() {
  const [count, setCount] = useState(0);

  const increment = useCallback(() => setCount(c => c + 1), []);
  const decrement = useCallback(() => setCount(c => c - 1), []);

  return (
    <div>
      <button onClick={increment}>+</button>
      <span>{count}</span>
      <button onClick={decrement}>-</button>
    </div>
  );
}

By wrapping increment and decrement with useCallback, their references remain stable across renders, preventing unnecessary re-renders in child components that receive these functions as props.([GeeksforGeeks][2])

SHOW VARIABLES LIKE 'validate_password%';

If disabled, this will return an empty result set.

Then reload AppArmor:

sudo apparmor_parser -r /etc/apparmor.d/usr.sbin.mysqld

Install phpMyAdmin along with necessary PHP extensions:

sudo apt install phpmyadmin php-mbstring php-zip php-gd php-json php-curl

prime-run glxinfo | grep "OpenGL renderer"

You should see:

#include "ScopedPointer.h"

void loadData() {
    ScopedArray<char> buffer(new char[1024]);

    if (someCondition()) {
        return; // no memory leak!
    }

    // buffer is auto-deleted when going out of scope
}

Some legacy APIs require raw pointers. You can still use get():

A deep copy duplicates the actual data pointed to, not just the pointer.

class Deep {
public:
    int* data;

    Deep(int val) {
        data = new int(val);
    }

    // Copy constructor for deep copy
    Deep(const Deep& other) {
        data = new int(*other.data);
    }

    // Assignment operator for deep copy
    Deep& operator=(const Deep& other) {
        if (this != &other) {
            delete data;
            data = new int(*other.data);
        }
        return *this;
    }

    ~Deep() {
        delete data;
    }
};

document.querySelector('form').dataset.start = Date.now();

Then send that timestamp with the form, and on the server:

Use Postman or curl:

curl http://localhost:3000

• Definition: Represent two states: HIGH (ON) and LOW (OFF).
• Usage: Turning LEDs on/off, reading button states.

• Definition: Varying signals that can represent a range of values.
• Usage: Reading sensor data (e.g., temperature, light intensity).

let video;
let detector;
let detections = [];

function setup() {
  // Create the canvas to match the video dimensions
  createCanvas(640, 480);
  // Capture video from the webcam
  video = createCapture(VIDEO);
  video.size(640, 480);
  video.hide();

  // Load the pre-trained COCO-SSD model
  cocoSsd.load().then(model => {
    detector = model;
    console.log("Model Loaded!");
    // Begin detecting objects every frame
    detectObjects();
  });
}

function detectObjects() {
  detector.detect(video.elt).then(results => {
    detections = results;
    // Continue detection in a loop
    detectObjects();
  });
}

function draw() {
  // Draw the video
  image(video, 0, 0);

  // Draw detection boxes and labels if available
  if (detections) {
    for (let i = 0; i < detections.length; i++) {
      let object = detections[i];
      stroke(0, 255, 0);
      strokeWeight(2);
      noFill();
      rect(object.bbox[0], object.bbox[1], object.bbox[2], object.bbox[3]);
      noStroke();
      fill(0, 255, 0);
      textSize(16);
      text(object.class, object.bbox[0] + 4, object.bbox[1] + 16);
    }
  }
}

• Setup: The setup function initializes the canvas and video capture. The video is hidden by p5.js’s default element so that we can draw it onto the canvas manually.
• Model Loading: We load the COCO-SSD model asynchronously. Once the model is ready, we start continuous object detection by calling detectObjects().
• Detection Loop: The detectObjects function uses the loaded model to analyze the current video frame and stores the detection results. It recursively calls itself so that new frames are analyzed continuously.
• Drawing: In the draw loop, the video feed is displayed and for each detected object, a rectangle and label are drawn. The bounding box coordinates and object class are provided by the model.

npm install -g @tauri-apps/cli

We’ll start by creating a new Svelte project. You can use a template via degit:

#ifndef DSL_PARSER_H
#define DSL_PARSER_H

#include "Lexer.h"
#include "AST.h"
#include <memory>

class Parser {
public:
    Parser(Lexer& lexer);
    std::unique_ptr<ASTNode> parseExpression();

private:
    Lexer& lexer;
    Token currentToken;

    void eat(TokenType type);
    std::unique_ptr<ASTNode> factor();
    std::unique_ptr<ASTNode> term();
};

#endif // DSL_PARSER_H

Implementation: Parser.cpp