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Understanding React Context API: A Practical Guide

React's Context API helps in sharing data across components without prop drilling.
Context is useful for managing authentication, themes, and language settings.
It's recommended for state accessed by many components and to avoid deep prop passing.
Context is not suitable for high-frequency updates or complex state management.
Creating a context involves using createContext, Provider, Consumer (older way), and useContext hook.
Provider wraps the component tree to pass down values, while useContext simplifies access to context values.
A real-world example shows creating an AuthProvider, custom hooks like useAuth, and wrapping the app.
Best practices include splitting contexts logically, using custom hooks, and keeping context values minimal.
Avoid using context for frequently updating values.
The Context API is a clean way to manage state for things like auth and themes in React.

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Medium

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Progressive Web Apps (PWA)- in Action

Progressive Web Apps (PWA) work for every user, regardless of browser choice, employing progressive enhancement.
PWAs are responsive, fitting various form factors like desktop, mobile, and tablet.
They are connectivity independent, functioning offline or with poor connectivity through service workers.
PWAs feel like native apps with app-style interactions and navigation.
Always up-to-date due to the service worker update process, PWAs are served via HTTPS for security.
They are easily re-engaging through features like push notifications and can be installed on the home screen.
PWAs are easily shareable via URL and don't need complex installation.
Service workers act as a proxy between the app and the network, enabling offline functionality.
The Web App Manifest provides metadata about the app and guides how the app should behave when installed.
HTTPS is crucial for security and enabling service worker functionality.
PWAs combine the reach of the web with the user experience of native mobile apps, representing the evolution of web applications.
A complete PWA structure has been created, including all essential components like main HTML structure and PWA components.
PWAs benefit users by delivering a native app-like experience on the web.
Developers can leverage PWAs to create engaging, reliable web experiences.
The transition to PWAs marks a significant paradigm shift in web development.
PWA development focuses on enhancing user experiences through app-like functionality on the web platform.

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Medium

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Stop Thinking in Controllers — Compose PHP from Behavioral Arcs

Controllers in PHP don't effectively organize code as they narrate a linear story in CRUD operations.
The traditional MVC architecture is struggling to accommodate real user behaviors, which are dynamic and non-linear.
Users don't interact in isolated controllers but rather follow arcs of behavior with various intentions and actions.
Real user activities involve flows, detours, loops, and indecisive moments, contrary to the structured nature of controllers.
Behavioral arcs in user actions are complex and continuous, challenging the conventional PHP controller paradigm.

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Medium

102

## Automating Excel Reports with C# and ChatGPT: A Developer's Guide

The article discusses automating Excel report generation using C# and ChatGPT.
Reading Excel data involves using ClosedXML library to process data into a DataTable.
Utilizing the ChatGPT API to generate insights based on the data read from Excel.
Building reports and exporting them with ClosedXML library in C#.
Key automation patterns include scheduled execution, template engine usage, error handling, and dynamic inputs handling.
ChatGPT prompts for development are provided, including generating C# code and handling exceptions.
Best practices mentioned are storing API keys securely, using 'using' statements for resource cleanup, validating ChatGPT outputs, and implementing retry logic for API calls.
This automated approach reduces manual Excel work significantly while enhancing flexibility, especially for intermediate C# developers with the assistance of ChatGPT.
It is emphasized to test the generated code and ensure secure handling of sensitive data at all times.

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Dev

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AltSchool Of Engineering Tinyuka’24 Month 4 Week 4

The article focused on JavaScript fundamentals, covering key aspects such as variables, data types, user interaction, type conversions, operators, conditional branching, loops, functions, and variable scope.
It explained the various data types in JavaScript, including numbers, strings, booleans, undefined, BigInt, objects, null, and the concept of type checking.
User interaction methods like alert(), prompt(), and confirm() were discussed, highlighting their roles in communicating with users through modal dialog boxes.
The article also touched upon type conversion in JavaScript, including string, numeric, and boolean conversions, providing examples for each.
Operators in JavaScript, such as mathematical, comparison, logical, bitwise, null coalescing, and optional chaining operators, were outlined with explanations and examples.
It elaborated on comparison operators like ==, ===, !=, >, <, >=, <=, and logical operators including ||, &&, and !, showcasing their functions.
The article concluded with a message of gratitude, encouraging further exploration of the concepts discussed and inviting feedback from readers to foster engagement.

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Dev

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Restarting My Java Journey: From Exam-Oriented Learning to Becoming a Real Developer

The author reflects on their Java programming journey, starting with exam-focused learning and transitioning to becoming a professional developer.
Initially, the focus was on passing exams, memorizing syntax, and completing assignments without a deep understanding.
A shift in mindset led to a decision to restart learning Java with a focus on problem-solving and practical application.
The author's new approach includes revisiting core Java concepts, practicing advanced Java with real projects, and delving into Hibernate and Spring frameworks.
Beyond Java, the author aims to grow as a developer by learning software development principles and preparing for interviews.
The author shares their journey through a blog to stay accountable and inspire other beginners.
A 21-Day Preparation Challenge has been initiated covering Java concepts, problem-solving, communication skills, and interview readiness.
The author emphasizes the importance of intent to improve, consistency, and honesty in the learning process.
The narrative encourages connections and sharing of experiences among individuals following a similar path.
The journey spans from exam-oriented learning to skill-based learning, highlighting the significance of continuous improvement.
The author invites engagement and mutual growth within the learning community.
The journey signifies the importance of transitioning from exam-focused learning to skill-based development for personal and professional growth.

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Self-Learning-Java

LangChain4j: Powerful AI & LLM Features for Java Developers

LangChain4j brings modern AI capabilities to Java applications with a wide range of features.
Integrations include 15+ LLM providers such as OpenAI, Google Vertex AI, Hugging Face, and more.
It supports 20+ vector stores like Pinecone, Redis, Chroma, and various embedding models.
LangChain4j also offers 5+ image generation models and scoring and reranking models for retrieval results.
Document processing and RAG capabilities involve importing from multiple sources, smart text splitting, embedding generation, and re-ranking.
AI services and tools provided by LangChain4j include a high-level LLM API, prompt templating, function calling, and text classification.
The platform offers features for chat and memory management, utilities like output parsing, token counting, and Kotlin coroutine support.
Multimodal support allows text and image inputs for vision-capable models.
LangChain4j simplifies the development of AI-powered Java applications, including chatbots and RAG systems, within the JVM ecosystem.

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Self-Learning-Java

222

LangChain4j: Supercharge Your Java Application with the Power of LLMs

LangChain4j is a Java library that helps developers easily connect their applications with language services like OpenAI or Google.
It was created in early 2023 to provide Java developers with tools that were previously limited in the language space.
LangChain4j offers a simple way to connect to various language services and storage providers, reducing the need to learn multiple systems.
It currently supports over 19 language service providers and more than 20 text storage services.
The library includes ready-to-use tools for creating prompts, managing chat history, building question-answer systems, and more.
It also provides easy-to-follow examples and works seamlessly with popular Java frameworks like Spring Boot and Quarkus.

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Self-Learning-Java

231

Quickly Explore Table Schema using bq CLI

The "bq show –schema" command is used in the bq CLI tool to display the schema of a specific BigQuery table.
It provides a quick overview of columns and data types, can help validate table structure before writing queries, and is useful for scripting or automating metadata checks.
The syntax is "bq show --schema [PROJECT_ID].[DATASET].[TABLE]".
If the default project is set via gcloud, the command simplifies to "bq show --schema [DATASET].[TABLE]".
It improves readability and reduces errors, especially in scripts.
An example schema command without the Project ID is "bq show --schema [DATASET].[TABLE]".
A sample schema output for a table is provided, showing column names, types, and modes.
Users can utilize tools like jq to format the output for better readability.

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Self-Learning-Java

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Spring Boot and Prometheus Integration Step by Step Guide

Prometheus is an open-source monitoring and alerting toolkit used in modern software systems like microservices and cloud-native applications.
It works by scraping metrics from instrumented applications at defined intervals and storing them in a time-series database.
Spring Boot Actuator provides various application metrics such as memory usage, thread count, CPU usage, etc., which can be integrated with Micrometer and Prometheus.
Enabling Prometheus in a Spring Boot app allows monitoring, alerting, visualization of metrics in Grafana, tracking usage patterns, and debugging with data-backed insights.
Common use cases for Prometheus integration include monitoring API response times, tracking active threads or connections, checking JVM memory stats, measuring custom business metrics, and enabling auto-scaling decisions.
The step-by-step guide involves creating a Maven project, updating the pom.xml file with dependencies, configuring the application.yml file, defining controller and main application classes, and running the application.
Additionally, configuring Prometheus to read metrics from the Spring Boot app involves defining endpoints in the prometheus.yml file and starting the Prometheus server.
Further steps include running Prometheus server, viewing configured targets, and querying metrics like process_cpu_time_ns_total from the Java Spring Boot application.
Micrometer is highlighted as a metrics instrumentation library for Java applications, offering a unified API to collect and expose application metrics.

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Medium

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State-Sponsored Hackers Target Critical Infrastructure in Asia

State-sponsored hackers are targeting critical infrastructure in Asia, posing a serious threat to national security.
Attacks are highly coordinated efforts involving advanced persistent threats (APTs) and have increased significantly between 2022 and 2024.
Report shows a 45% increase in state-sponsored cyberattacks targeting Asian infrastructure.
Taiwan experienced a cyber intrusion in October 2023, linked to a Chinese state-backed group known as APT41.
Several state-sponsored groups, such as APT32, have consistently targeted Asian infrastructure using advanced techniques.
These actors employ methods like spear-phishing, zero-day exploits, and custom malware designed for industrial environments.
An emerging trend is the use of artificial intelligence to enhance social engineering attacks.
Geopolitically, Asian nations are treating cyberattacks as strategic-level threats.
Amidst rising tensions, cyber campaigns could intensify in regions like the South China Sea, the Taiwan Strait, and the Korean Peninsula.
Infrastructure attacks may be used as preludes to or replacements for physical confrontations.
The absence of international norms on cyber conduct allows state-sponsored hackers to exploit digital warfare gray areas.
The future of Asian infrastructure security depends on effective government actions and cyber resilience measures.
Protecting critical systems from hostile nation-states is crucial for national security, economic stability, and public safety.

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Dev

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Rust Ownership Mastery: The Zero-Cost Safety Revolution

Rust's ownership model revolutionizes memory safety by providing compile-time guarantees instead of runtime overhead.
The ownership model ensures one owner per value, automatic cleanup when owners go out of scope, and contracts enforced by the compiler.
Rust's ownership model consists of ownership, borrowing, and lifetimes, offering C-level performance with Haskell-level safety.
Eliminating entire bug categories like double frees and data races, Rust guarantees memory safety with zero runtime overhead.
The borrow checker, despite initial intimidation, aids in catching subtle bugs, with tools like rust-analyzer providing support.
Rust's ownership model guides better software architecture, clear API contracts, modular boundaries, and safer concurrency.
Key takeaways include learning ownership patterns, leveraging zero-cost abstractions, and considering Rust for various applications.
Rust's ownership model offers productivity gains, clearer APIs, and reduced debugging time, making it suitable for new projects and team efficiency.
The learning curve for Rust's ownership model pays off with increased productivity and safety benefits, suitable for new and existing projects alike.
Rust's ownership model benefits not only systems programming but also web backends, CLI tools, WebAssembly, and game development for performance and reliability.

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Medium

175

Simple AI Projects Students Can Build with Python

Students with basic Python knowledge can build simple AI projects.
These projects are easy to complete in a weekend and offer valuable real-world AI insights.
10 simple AI project ideas are outlined, emphasizing using Python.
Projects include building chatbots, image recognition models, sentiment analysis tools, recommendation engines, digit recognition models, sentiment analysis on tweets, HR tool simulations, object detection models, reinforcement learning projects, and a startup project.
Chatbots start with rule-based bots and progress to NLP-powered bots.
Image recognition project teaches image preprocessing, CNNs, and more.
Sentiment analysis project combines machine learning and NLP, offers a bonus idea of creating a web interface.
Recommendation engine project teaches similarity metrics and presents a bonus idea of creating a fun quiz.
Digit recognition project is visual and satisfying, with a bonus idea of creating a live prediction feature.
Sentiment analysis on tweets project involves text cleaning, polarity scores, and real-world APIs use, with a bonus idea of visualizing results with charts.
HR tool simulation project teaches NLP concepts like Named Entity Recognition, with a bonus idea of extracting insights from resumes.
Object detection project is real-time and visual, offering a bonus idea of implementing face recognition.
Reinforcement learning project offers a gentle introduction to the concept, with a bonus idea of recording gameplay.
Startup project combines computer vision and web scraping, with a bonus idea of adding a product classifier.
These projects can enhance Python skills and are beneficial for both learning and showcasing abilities.
Students can further customize these projects by adding bonus features and functionalities.
Building these AI projects can be a great addition to a student's resume or GitHub profile.
The projects cover a wide range of AI concepts and tools, making them a comprehensive learning experience.

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Medium

630

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I Don’t Fear AI Replacing Me. I Fear People Who Refuse to Learn It.

The author expresses fatigue towards the fear of AI replacing people.
The real fear lies in people who refuse to learn AI and fall behind.
AI is viewed as a mirror that reflects one's curiosity, adaptability, and openness to change.
Initially intimidated by terms like 'LLMs' and 'Neural Networks,' the author embraced learning AI.
The shift was from worrying about AI dominance to exploring its possibilities.
Jobs are not eradicated by AI but by individuals resistant to evolving.
Those who adapt, like designers using AI tools or writers employing LLMs, benefit greatly.
The key is to understand how AI can enhance creativity and performance.
The threat isn't AI itself but being stagnant in a changing world.
The author highlights the importance of starting to learn and engage with AI, irrespective of being 'ready'.
AI is not exclusive to scientists but also for those willing to grasp patterns and innovate.
The author transitions from fearing AI to eagerly collaborating with it for a brighter future.
The call is to approach the future with courage and collaboration, rather than fear.

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Medium

189

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Diary of a Tech Newbie (Ep. 5): Choosing my Area of Focus (Artificial Intelligence)

Received advice in a tech meeting to choose a tech focus area.
Initially unsure about which area to choose due to limited tech industry knowledge.
Decided to merge health and tech, focusing on digital health and telemedicine.
Shifted focus to artificial intelligence (AI) as it was emerging in the fintech industry.
Researched AI's use cases in healthcare, leading to a postgraduate program in public health tailored to AI.
Received a scholarship from Africa Agility Foundation to develop skills in AI/ML.
Continues to contribute to promoting the AI niche while honing skills and capacity.
Plans to share lessons learned and technical skills in subsequent episodes.
Open to mentorship, internship, conferences, research collaborations, and other opportunities in the AI niche.

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