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I Made a TUI in C... and regretted it

Working on a TUI in C, the writer found it challenging due to the low-level nature of the language, requiring meticulous memory management and manual control of program features.
Ncurses, a popular C library for text-based user interfaces, provided essential tools but demanded intricate handling for even simple tasks, making UI updates a manual process.
Another library, cJSON, despite being a single file with about 5000 lines, played a significant role, highlighting the writer's heavy reliance on it for their TUI project.
Libcurl, used for network operations, required detailed manual setup for basic tasks like creating headers, showcasing the hands-on approach needed in C development.
Documentation for these libraries lacked modern user-friendly features, relying more on traditional text-based manuals, posing a contrast to more contemporary language frameworks.
The writer's motivation for choosing C and creating a TUI stemmed from a desire to challenge themselves and move away from tools that automate many aspects of development.
The article serves as a cautionary tale for beginners in C programming, as the writer acknowledges potential shortcomings and areas for improvement in the code.
The project involved handling HTTP requests, rendering menus from JSON data, managing tasks, and creating a functional text-based interface with navigation and task management features.
Despite the challenges and complexities faced, the writer successfully implemented a working TUI in C, emphasizing the manual effort required for tasks that might be more streamlined in higher-level languages.
The writer's decision to build the TUI in C was framed as a personal challenge to delve into the intricacies of low-level programming and to gain a deeper understanding of the technical nuances involved.
Overall, the article highlights the demanding nature of developing a text-based interface in C, showcasing the labor-intensive processes involved in handling UI elements and network operations within a TUI project.

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Medium

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CheckADevice.com fast, no-fuss online device testing tool

CheckADevice.com is a free online tool for testing hardware components of computers or mobile devices.
It allows real-time testing of webcams, microphones, keyboards, mice, and speakers for functionality.
The tool operates within the browser, eliminating the need for downloaded software and providing fast and seamless testing.
Future features will include internet speed tests, battery health checks, and advanced diagnostics.

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Hackernoon

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Why I Stopped Overthinking and Shipped My CSS Cheat Sheet

Perfection kills momentum.
The author stopped overthinking and finally shipped an Advanced CSS Selectors & Techniques Cheat Sheet.
The cheat sheet received 84 organic views and was found helpful by real people.
The author encourages others to stop waiting and just hit publish to learn and build confidence.

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Hackernoon

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Oracle’s New AI Platform Lets You Build Chatbots That Tell Medieval Tales

The article introduces beginners to Oracle Cloud Infrastructure (OCI) Generative AI service, covering creating an account, setting up the environment, and running the first AI task in Python.
OCI offers AI services like GPU infrastructure and GenAI-powered apps for tasks like text generation, summarization, and embeddings.
Generative AI in OCI has Large Language Models (LLMs) for various tasks, and users can fine-tune models with custom data sets and deploy them on dedicated AI clusters.
Models like Meta Llama and Cohere's Command R and R+ are accessible through OCI SDK in Python, Java, and Node.js.
Initial steps include creating an account, navigating the OCI Console, generating an API key, and creating a configuration file for authentication.
Setting up the environment involves installing necessary libraries in a virtual environment using tools like venv or conda.
Running the first AI task involves creating a Python script, setting up authentication with OCI Generative AI client, and interacting with model endpoints.
Examples are provided for using OCI models like Meta Llama and Cohere's Command R by composing chat requests and displaying the generated responses.
The article concludes by highlighting the steps for getting started with OCI Generative AI and encourages users to refer to the documentation for more information.

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Dev

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Alpha vs Beta Testing: Key Differences & Best Practices

Alpha and Beta Testing are crucial phases in software development that help ensure stable, high-quality releases by catching bugs and improving usability.
Alpha Testing is the initial testing phase conducted internally by developers and QA teams in a controlled environment, while Beta Testing involves real users trying the software in a real-world setting.
The goals of Alpha Testing include catching major functional bugs early, identifying usability issues, and ensuring core functionality works as expected.
In contrast, Beta Testing focuses on validating real-world performance, gathering user feedback for improvements, and ensuring scalability before the final release.
Alpha Testing is more about bug fixes and feature validation, while Beta Testing focuses on product refinements and usability improvements.
Key differences between Alpha and Beta Testing include the testers involved, the testing environment, goals, bug severity, test focus, and outcomes.
Tools such as bug tracking, testing automation, performance profiling, and API testing are essential for successful Alpha Testing, while user feedback, crash reporting, and feature flagging tools are crucial for Beta Testing.
Skipping Alpha Testing can increase risks and harm a product's reputation, emphasizing the importance of both testing phases in the software development lifecycle.
Beta Testing challenges include ensuring active user participation, effective feedback management, and analyzing diverse real-world conditions.
Choosing diverse Beta Testers representing the target audience is crucial for collecting comprehensive feedback and ensuring the product meets varying user needs.

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Medium

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Managing Server-Side Global State in Next.js 15+

The introduction of the App Router in Next.js 15 has changed the way developers structure and navigate applications.
Migrating from the Pages Router to the App Router requires restructuring your project directory and adjusting routing logic, but offers significant benefits in code organization and performance.
Next.js 15 introduces Server Components and streaming, improving performance by offloading tasks to the server and allowing incremental rendering of HTML.
The improved support for the native fetch API simplifies data fetching and integration with various APIs and data sources.

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Dev

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JavaScript Arrays: Essential Questions and Answers

JavaScript Arrays: Essential Questions and Answers
Arrays in JavaScript can be declared using brackets or the Array constructor function.
Key differences: Bracket notation is preferred over the Array constructor for array declaration.
Arrays store collections of data and are optimized for ordered collections.
Accessing elements in arrays is zero-indexed in JavaScript.
JavaScript arrays can be accessed using numeric indices.
Adding elements to an array can be done using .push() or .unshift() for end or beginning insertion.
.push(), .pop(), .shift(), and .unshift() are methods for adding/removing elements in arrays.
Looping through arrays can be done with for loop, .forEach(), and .map().
Sparse arrays in JavaScript have empty slots instead of actual values.

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Dev

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DAY 5 In Java create an object,

Step 1: Define a Class
Step 2: Create an Object
Explanation:
Rules for Creating a Class

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Medium

355

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Using Subsearches

To filter data after aggregation, use the HAVING clause.
A subsearch is a nested search within a primary (outer) search, enclosed in square brackets [ ].
Performance considerations: Subsearches are limited to 10,000 results and 60 seconds by default.
The append command in Splunk appends the results of a subsearch to the main search results.

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Medium

143

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Navigation - NavigationView in WinUI 3

NavigationView control provides top-level navigation for your app and supports both top and left navigation styles.
Navigation patterns in NavigationView include top, left, LeftCompact, and LeftMinimal navigation.
Different navigation styles are achievable by configuring the PaneDisplayMode property of NavigationView.
NavigationView's adaptive behavior allows for seamless transitions between display modes based on available screen space.
You can customize the NavigationView layout by utilizing properties like FooterMenuItems, PaneFooter, PaneTitle, PaneHeader, and PaneCustomContent.
Navigation items in NavigationView are part of the same selection model and can be handled using events like ItemInvoked and SelectionChanged.
Backwards navigation in NavigationView requires handling the BackRequested event manually.
Hierarchical navigation structures in NavigationView can be achieved using MenuItems and MenuItemsSource properties.
Selective item highlighting and event handling are essential in managing navigation and hierarchy in NavigationView.
Customizing the NavigationView appearance can be done by overriding theme resources and adjusting layout settings.

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Logrocket

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How to set up TypeScript with Node.js and Express

TypeScript with Node.js and Express is beneficial for managing complex applications, improving code strength and clarity, and enhancing collaboration and scalability.
TypeScript offers benefits like improved code strength, collaboration, tooling, IDE support, and broader compatibility.
Express TypeScript involves writing Express server code in TypeScript for type checking, auto-completion, and better documentation.
TypeScript with Express enables static typing for catching bugs, defining interfaces for requests/responses, and predictability.
Setting up a TypeScript Express project involves steps like initializing the project, configuring TypeScript, and structuring the project.
Environment configuration in TypeScript involves loading and typing environment variables using packages like dotenv.
Controllers in TypeScript manage CRUD logic, with error handling and RESTful routes defined in separate files.
Global error handling middleware in TypeScript Express catches errors in routes/controllers for consistent error responses.
Linting with ESLint and formatting with Prettier maintain code quality and consistency in TypeScript projects.
Testing with Jest in TypeScript Node.js Express projects ensures application behavior and code maintainability with fast, parallel tests.

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Codecondo

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Supercharge Your Development Workflow: Mastering GitHub Copilot for Data, Express.js, and Static Websites

GitHub Copilot is an AI-powered tool by GitHub and OpenAI that suggests code as you type, saving time and reducing errors for developers.
It accelerates workflows and helps in learning new techniques while working with data, Express.js, and static websites.
To start using GitHub Copilot, install the extension in your favorite code editor, link your GitHub account, and enable suggestions.
GitHub Copilot can fetch and manage data efficiently, offering suggestions for handling HTTP requests and filtering data in JavaScript.
For Express.js development, it can assist in creating server middleware like request logging, following Express.js conventions and making development faster.
In static website development, GitHub Copilot can generate HTML and CSS code quickly for building layouts, ensuring speed, consistency, and learning opportunities.
By using GitHub Copilot, developers can speed up project development, maintain consistency in code quality, and enhance the learning process.
Whether you are a beginner or an experienced developer, GitHub Copilot can adapt to your needs and improve your coding experience.
Install GitHub Copilot today to boost your productivity and efficiency in coding, and share your tips or tricks in the comments to learn from others' experiences.

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Dev

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Build your Own Secure Chat App with Audio/Video calls for any business

Businesses can benefit from building their own secure chat app with audio/video calls to ensure privacy and seamless communication tailored to their needs.
Key reasons for businesses to use a secure chat app include data protection, compliance with regulations, increased productivity, seamless communication for global teams, and brand customization.
Essential features of a secure chat app include end-to-end encryption, real-time synchronization, high-quality audio/video calls, voice note messenger, group chat, AI chat features, file sharing, and cross-platform compatibility.
Steps to build a secure chat app involve defining business requirements, choosing the right technology stack, implementing secure authentication, developing messaging and calling features, integrating AI chat features, ensuring compliance and data privacy, and testing for optimization.
Industries such as healthcare, education, legal, finance, real estate, and entertainment use video call apps for various purposes like telemedicine, virtual learning, remote meetings, customer support, training, consultations, and collaborations.
After building the chat app, deployment on platforms like AWS, Google Cloud, or Azure is recommended for scalability and performance optimization, with regular updates and security patches to maintain efficiency and resilience against threats.
In conclusion, developing a secure chat app with audio/video calls is essential for businesses focusing on data security, team collaboration, and efficient communication, with the integration of advanced features ensuring privacy and productivity enhancements.

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Dev

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Error Handling in Go vs. C#: Trading Exceptions for Clarity

C# exceptions act like fire alarms, propagating up the call stack until caught.
Go treats errors as ordinary values, forcing developers to handle them immediately within the function.
Go has the 'panic' keyword for handling unrecoverable issues, closer to C#'s Environment.FailFast.
Go's error handling promotes transparency, resilience, and simpler codebases, but can be verbose and require manual effort for error context.

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Dev

313

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Building AI-Powered Applications in Laravel with Neuron AI

Laravel developers have the opportunity to integrate AI-powered solutions into their applications using frameworks like Neuron AI.
Memory and context are crucial for AI agents to maintain coherent conversations and make intelligent decisions.
Neuron AI provides an efficient way to handle chat history and memory, ensuring AI agents can maintain context.
Laravel developers can build scalable AI applications for customer support, personalized recommendations, data analysis, and documentation assistance using Neuron AI.

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