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A Comprehensive Guide to CSS Terminology

CSS is a powerful language that transforms HTML structures into visually stunning websites, with terminology that can feel overwhelming but becomes manageable with practice.
Mastering CSS terminology is key to creating user-friendly designs across all devices.
The guide covers core principles of CSS like the cascade, specificity, inheritance, and the box model.
Understanding the cascade involves knowing how styles are applied based on order and source, such as browser defaults, user styles, and author styles.
Specificity determines which styles take precedence based on a hierarchy of selectors like IDs, classes, attributes, and elements.
Inheritance in CSS allows child elements to inherit properties from their parents, reducing redundancy and ensuring consistency.
The box model defines how elements are structured with content, padding, border, and margin.
CSS syntax elements include selectors, declarations, rulesets, and at-rules that form the building blocks of CSS.
Properties and values in CSS control styling aspects like typography, layout, colors, measurements, and units.
Styling images in CSS involves using object-fit to control how images fit within containers and background images for decorative visuals.

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Medium

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The new Gemini 2.5 Pro is an absolute game changer

The new Gemini 2.5 Pro model has become a game changer in the field of AI.
Google has taken the lead in the LLM (Language Learning Model) race.
Gemini 2.5 Pro has surpassed Grok and is competing favorably in various areas.
The model exhibits impressive complex multi-step thinking capabilities.

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Medium

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Run AI Models Locally: Docker Desktop’s New AI Model Runner

Docker has introduced a new feature, AI Model Runner, in Docker Desktop.
AI Model Runner enables running large language models (LLMs) locally with a Docker-native experience.
It is currently available on macOS with Apple Silicon and will soon support Windows with NVIDIA GPUs.
AI Model Runner provides fast, simple, and integrated local-first development experience.

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Dev

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Touch Events (swipe) using Stimulus

The article discusses implementing touch events, specifically swipe, using Stimulus for web-apps designed for touch devices like phones and tablets.
It explores using touch events for carousels and tinder-like left and right card swipes, with code examples and explanations provided.
The HTML structure for carousel and swipe-card functionalities is shown, highlighting the data attributes and actions required.
The carousel controller in Stimulus handles next and previous functionality with circular navigation, ensuring the index stays within valid bounds.
For touch device support, the controller is extended with touchStart and touchEnd methods to track swipe gestures and navigate accordingly.
In the swipe-card feature, the inheritance concept is used by creating a base swipe_controller shared between carousel and swipe-card controllers.
The swipe-card controller manages swipe actions for liking or disliking cards, animating them off-screen, and utilizing Fetch API for backend requests.
Additional touchMove method is added for swipe-card controller to handle touchmove events, adding CSS animations to the cards based on touch movement.
Overall, the article demonstrates a structured approach to using Stimulus controllers for touch events, providing a scalable and reusable solution for touch-enabled web features.
It encourages feedback and suggestions for enhancing the implementation of Stimulus controllers with similar functionalities.

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Dev

335

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Are you using AI only to write code? You're missing out

AI is essential in software development beyond just writing code, transforming critical areas like CI/CD, documentation, PR reviewing, and system design.
Challenges in software development include CI/CD complexity, documentation debt, debugging bottlenecks, and system design challenges.
AI optimizes CI/CD pipelines by intelligently analyzing failures, connecting issues to patterns, and suggesting fixes for quicker recovery.
AI-enhanced debugging tools help identify performance issues in distributed systems, reduce root cause analysis time, and enhance developer productivity.
AI-powered system design tools analyze application interactions, suggest optimizations for scalability, and aid in building efficient architectures.
PR reviews benefit from AI models that track code dependencies, understand architectural patterns, and provide context-aware intelligent feedback.
AI-generated documentation solves the long-standing documentation debt issue by automating code documentation and providing interactive learning experiences.
AI-driven planning improves project management by automating backlog management, predicting bottlenecks, and generating accurate PRDs aligned with development requirements.
Integrating AI into project planning ensures better alignment between product vision and execution, leading to increased efficiency and improved development velocity.

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Medium

183

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Why Integrate AI in Software Development Lifecycle Now?

Developers are turning to AI in software development to solve real problems.
AI can automate repetitive code, tedious documentation, and streamline testing cycles.
Integrating AI in the development workflow allows companies to work smarter and faster.
AI-assisted software development upgrades developers rather than replacing them.

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Dev

165

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Redoed #5: Building a Markdown editor with CodeMirror and React

The article guides on building a Markdown editor using CodeMirror and React with an emphasis on integrating with other tools.
Vite and Bun are used to set up the React app in the project's root directory, with frontend code residing in a dedicated folder.
Key dependencies include @uiw/react-codemirror for CodeMirror integration and react-markdown for Markdown previewing.
CodeMirror setup involves creating a TypeScript file, defining highlight styles for Markdown, and configuring themes.
The core editor component in React uses useState and useCallback for managing Markdown content and text changes.
For CodeMirror initialization, useCodeMirror is employed to handle state, extensions, syntax highlighting, themes, and onChange events.
Rendering the Markdown preview involves using ReactMarkdown to convert Markdown text to HTML with support from remark-gfm.
Additional components like Header are created to enhance the editor interface, with functionalities planned for future enhancements.
Bringing the editor and header components together in App.tsx streamlines the overall application architecture.
Development is simplified with the 'bun run dev' command, showcasing the visual appearance and progress made in building the Markdown editor.

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Medium

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The Mechanics Behind How Java Handles Polymorphism at Runtime and Compile-Time

Compile-time polymorphism in Java, specifically method overloading, is handled by the Java compiler based on method signatures and parameter types.
During compile-time, the compiler matches method signatures and generates bytecode, locking in the method calls without considering the object's actual type.
Java compiler uses method names and their signatures for method linking, excluding the return type from consideration.
Automatic type conversion is utilized by the compiler when choosing between overloaded methods.
Method overloading decisions are made by the compiler without runtime lookups, following a specific order of matching criteria.
Runtime polymorphism in Java involves method overriding, where a subclass provides its implementation of a method from a parent class.
Dynamic method dispatch in Java occurs at runtime, with JVM determining the specific method to execute based on the actual object type.
Vtables are used by JVM to map method names to memory addresses for fast method lookup during runtime.
Java's polymorphism distinguishes between compile-time decisions (method overloading) and runtime decisions (method overriding) for efficient and flexible object-oriented behavior.
The compiler's role is to work with method signatures for static decisions, while the JVM leverages vtables and object types for dynamic method dispatch.

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Inkbotdesign

30+ Best Web Design Resources for Developers

The article highlights the importance of using quality web design resources to enhance efficiency, creativity, and competitiveness in web development.
It emphasizes the significance of accessing tools like Behance, Dribbble, and Awwwards for design inspiration and showcases their key features.
Coding resources like GitHub, Stack Overflow, and CodePen are recommended for collaboration, support, and quick prototyping in web development.
Graphic design tools such as Adobe Creative Cloud, Sketch, and Figma are praised for their capabilities in creating visually appealing designs.
Popular web development platforms like WordPress, Wix, and Squarespace are discussed for their user-friendly interfaces and versatility in creating diverse websites.
UI/UX design resources like InVision, Sketch App Sources, and Adobe XD Resources are highlighted for their prototyping and collaboration features.
Typography tools such as Google Fonts, Font Awesome, and Adobe Fonts are suggested for enhancing design aesthetics and user experience.
Stock image libraries like Unsplash, Shutterstock, and Pexels are recommended for accessing high-quality images and videos for creative projects.
Colour palette generators like Coolors, Adobe Color Wheel, and Color Hunt are lauded for simplifying the process of creating visually appealing colour schemes.
SEO tools such as Google Search Console, SEMrush, and Moz are discussed for improving website visibility and search engine rankings.
Web hosting services like Bluehost, SiteGround, and HostGator are suggested for reliable hosting solutions with various features to support websites.
Responsive design testing tools including Responsively App, BrowserStack, and CrossBrowserTesting are recommended for ensuring websites are optimally displayed across devices.
Web accessibility resources like WAVE, Axe Browser Extension, and WCAG Guidelines are highlighted for creating inclusive websites catering to diverse user needs.
Collaboration and project management platforms like Trello, Asana, and Slack are endorsed for facilitating team communication, task assignment, and project tracking.
Learning platforms such as Udemy, Coursera, and LinkedIn Learning are commended for offering a wide range of courses to enhance skills and knowledge in web design.

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Medium

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10 Common Java Mistakes Even Experienced Developers Make

Java developers, both experienced and newbies, often make common mistakes.
Ignoring exceptions and not handling error messages is a prevalent mistake.
Using outdated collections like Vector and Hashtable is discouraged.
Storing sensitive information like database credentials and API keys in plain sight is a serious security error.

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The Pragmatic Engineer

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The Pulse #128: Mishandled security vulnerability in Next.js

A vulnerability allowed bypassing of authentication at the middleware layer in the popular React framework.
Cloudflare stepped in with a security fix after no meaningful communication from Vercel.
Meta cut CPU utilization across its ads infrastructure 20%, with a one-character change.
Google buys Wiz for $32B in biggest-ever tech acquisition.

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Logrocket

421

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Faceted filtering for better ecommerce experiences

Faceted filtering in ecommerce provides users with the ability to quickly refine search results by selecting attributes from predefined categories, improving the overall search experience.
Faceted filtering differs from traditional search methods by allowing users to select multiple attributes simultaneously, leading to more relevant and precise search results.
Filters refine data based on specific attributes, while facets categorize information into buckets like product type or color in a more detailed manner.
Best practices for faceted filtering include using clear labels, prioritizing relevant facets, displaying applied filters, limiting options, providing search functions, allowing users to save filters, and testing with real users.
Common pitfalls to avoid with faceted filtering include performance issues, overlapping facets, non-persistent filters, zero results, and lack of a reset option.
Advanced methods of faceted filtering involve dynamic faceting that adapts based on the user's search context, AI-powered filtering using historical data, and interactive filter controls like sliders and toggles.
Faceted filtering is crucial for ecommerce websites to enhance user experience and improve search efficiency, helping users find what they need without getting overwhelmed by numerous options.

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Javacodegeeks

367

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Multi-Tenancy in Spring Boot: Sharding vs. Schema Isolation

Multi-tenancy in Spring Boot is vital for SaaS platforms serving multiple customers, allowing data isolation for each tenant.
The article discusses two common multi-tenancy approaches: Schema-Based Isolation and Database Sharding.
Schema-Based Isolation involves each tenant having a separate schema within the same database, enhancing data isolation.
Implementation in Spring Boot includes using Hibernate Multi-Tenancy to switch schemas dynamically based on requests.
Database Sharding, on the other hand, involves all tenants sharing a single database with partitioning by tenant-specific identifiers.
Configuring a Hibernate Tenant Filter allows automatic filtering of query results based on the tenant_id in Database Sharding.
Schema-Based Isolation provides strong data isolation but comes with operational overhead and potential scaling issues.
Database Sharding offers scalability benefits but compromises on data isolation and may face performance bottlenecks.
Choosing the right strategy depends on priorities; Schema-Based Isolation is ideal for isolation and compliance, while Database Sharding suits scalability and efficiency.
Ultimately, the chosen multi-tenancy strategy should align with business requirements, compliance needs, and operational capacity.

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Medium

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Android Going Closed-Source? No, But Google’s Walled Garden Is Real!

Google has confirmed that Android development will now be conducted entirely internally.
The source code will still be publicly available, but the development process itself will no longer be open.
Android has always had a mix of open-source and closed-source components.
The gradual shift towards a more closed ecosystem is evident in the Android platform.

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Dev

219

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Handling rate limits of OpenAI models in Java using Guava, JTokkit

Handling rate limited APIs optimally is crucial for faster execution of parallel requests, and OpenAI imposes request rate limit and token rate limit.
Exponential Backoff is used to handle failed requests by retrying after increasing time intervals to prevent continuous retries.
The Token Bucket Algorithm controls requests by allowing them only if enough tokens are available in a bucket that fills at a constant rate.
Tokenizing the input and estimating output tokens are essential steps before sending requests to the OpenAI Responses API.
Guava's RateLimiter class is used to manage token and request rate limits efficiently in Java applications.
Backoff strategies are employed to handle situations where rate limits are not met, and requests need to be retried after a delay.
The article presents code examples using the openai-java, JTokkit, and Guava libraries for implementing rate limit handling in Java applications.
Dependencies for these libraries can be added through Maven, and the code example provided in the article can be used for simulation.
The article also suggests resources for further reading on OpenAI rate limits, libraries used, and the Token Bucket Algorithm.
Readers can explore different scenarios like changing request limits, token limits, and retry mechanisms for practical understanding.

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