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9 Must-Know REST API Design Principles For Developers

REST APIs are essential for seamless communication between clients and servers, favored for web and mobile applications.
Good API design is crucial for performance and usability, avoiding confusion, inefficiency, and maintenance issues.
Following REST API best practices leads to intuitive, secure, and scalable web services.
Key principles include adhering to HTTP methods, focusing on resource nouns in URLs, using correct status codes, and providing clear error messages.
Input validation, versioning, pagination, filtering, and sorting are essential aspects of REST API development.
HATEOAS guides clients with links in responses, enhancing API self-documentation.
Security measures like HTTPS encryption, authentication, and authorization are vital for API protection.
Adhering to these best practices ensures creation of scalable, maintainable, and user-friendly APIs.
Java Spring Boot examples provided in the article offer practical insights for implementing REST API design principles.

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Juris Q&A: A Framework for Developers Who Hate Frameworks

Existing frameworks focus on computer efficiency rather than human cognition, creating cognitive overload.
Juris offers an intent-based design, avoiding complexity and allowing developers to focus on expressing intent.
Juris simplifies development by sidestepping performance problems inherent in sophisticated frameworks.
It provides debuggable intent, allowing developers to test and debug components without framework specific tools.
Juris enables seamless SSR by utilizing object-based components that work consistently on server and client.
The framework's performance outperforms popular frameworks by simplifying implementations and eliminating bottlenecks.
Juris's compatibility with the JavaScript ecosystem enhances development flexibility and access to libraries.
The framework prioritizes simplicity, using functions without complex patterns for state management.
Juris supports unlimited composition patterns and automatic dependency tracking across components.
Developers can choose between Juris core for stability and JurisKit for advanced features.

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Dev

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Python Fundamentals: repr

The article discusses the importance of mastering __repr__ in Python for system observability, security, and data governance.
__repr__ defines the official string representation of an object in Python, aiming to provide an unambiguous developer-focused representation.
Real-world use cases of __repr__ include logging incoming requests, asynchronous task queues, data validation, and CLI tools.
__repr__ integrates with key Python tools such as mypy, pytest, pydantic, logging, dataclasses, and asyncio.
Code examples show how to customize __repr__, mask sensitive data, and enhance immutability.
Performance considerations involve optimizing __repr__ for high-volume systems, efficient string interpolation, and caching computed values.
__repr__ must be carefully implemented to avoid security vulnerabilities by masking sensitive data and preventing code injection.
Testing __repr__ involves unit tests, property-based testing, and static type checking with mypy.
Common pitfalls like infinite recursion, exposing sensitive data, and lack of testing are highlighted.
Best practices for __repr__ include type-safety, separation of concerns, defensive coding, modularity, automation, and documentation.

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«My New Path»

The writer relied on freelancing to cover expenses, gradually building their account and clientele.
They ignored platform rules by completing assignments for students, leading to a ban.
Initially facing a temporary suspension, the ban later became permanent after a review.
Despite losing their progress, the writer sees this as a new beginning.
They plan to explore new ventures, share their journey, and welcome others to join them.
Interested individuals can follow their updates on Telegram at @serquor_devlog.
Hashtags for the post include #vlog, #freelance, #life, #story, #programming, and #army.

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Medium

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The Vibrant Culture of Punjab

Punjabi music is characterized by energetic beats and soulful melodies, with Bhangra being a prominent folk dance that showcases dynamic movements and infectious energy.
Gidda and Sufi music are also cherished components of Punjabi culture, offering a diverse musical experience.
Punjabi cuisine is renowned for its rich flavors and spices, featuring traditional delicacies like sarson ka saag, makki di roti, butter chicken, tandoori chicken, and lassi.
Festivals like Baisakhi, Diwali, Holi, and Lohri are celebrated with great fervor in Punjab, adding to its cultural vibrancy.
Punjabi culture is deeply rooted in tradition, emphasizing the significance of attires like salwar kameez and turbans, along with values like respect for elders and community.
The warmth, hospitality, and lively spirit of Punjabi culture make it an attractive destination for tourists and a source of pride for its people.

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Dev

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I Stopped Using Try-Catch in TypeScript and You Should Too

The article discusses the author's shift from using try-catch blocks to returning errors in TypeScript for better error handling.
By returning errors explicitly, the author finds improved clarity, error context, and granular error handling.
The article introduces the Result type and demonstrates its usage in async functions for more explicit error management.
Benefits highlighted include errors becoming part of the API, TypeScript enforcing error handling, granular error management, and improved composability.
The approach aims for transparency, safety, maintainability, and better debugging experiences in error handling.
Examples and patterns presented emphasize the importance of returning errors, handling unexpected errors separately, and relying on TypeScript for enhanced error management.
Real-world examples and production scenarios illustrate the practical advantages of returning errors over throwing them.
The article concludes by emphasizing the benefits of returning errors, such as honesty, safety, maintainability, and debuggability in code.
Ultimately, the author suggests trying this error-handling approach in projects to benefit from improved error management and user experience.

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Dev

336

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Programming During War: An Experience to Forget

Working on programming projects amidst a war zone creates a harrowing experience, with the constant threat of missiles and explosions.
A week into the conflict in Iran, the challenge is to maintain normalcy while dealing with intense emotions.
Despite the upheaval, the teamwork aspect of software development remains crucial, albeit with a changed approach.
Humor is used to alleviate tension among team members, indicating a collective effort to persevere.
Amidst evacuations, loss of connectivity, and concerns for loved ones, coding serves as a refuge from the chaos.
Focusing on coding tasks could be a coping mechanism to divert attention from the surrounding turmoil.
The hope remains for a return to peace and normalcy, as the situation continues to unfold.

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Prompt Coding: A New Logic System for AI-Driven Language Design

The article introduces the Prompt Header Recall System (PHRS) as a method for improving precision in interacting with AI through language models.
PHRS is inspired by software logic, aiming to streamline prompt design by treating them as modular linguistic commands.
It advocates for structured, reusable, and readable prompt design to enhance cognitive clarity and efficiency.
The system allows for the creation of prompt libraries that can be audited, scaled, and reused across time and team.
It emphasizes the importance of pattern, boundary, instruction, and clean recall in prompt design.
The article articulates the difference between simple and complex prompts, highlighting the advantages and disadvantages of each.
It illustrates examples of complex prompts and introduces the concept of a 'super prompt' for detailed and advanced instructions.
The article discusses the use of logic controllers such as AND, OR, NOT, XOR, IF/ELSE, and SWITCH/CASE to structure prompts effectively.
It emphasizes the significance of sandbox testing to ensure the integrity and stability of complex prompts before integration.
The article presents a strategic approach to prompt design, likening it to logic systems and pseudo-coding for effective communication with AI.
It concludes by positioning 'Prompt Coding' as a transformative framework that elevates prompt design into a structured discipline akin to software development.

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273

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Unlocking the Power of No-Code AI:

ActlysAI is a no-code AI platform that allows users to leverage artificial intelligence without technical expertise.
The platform simplifies AI model creation, deployment, and management through a user-friendly interface and pre-built models.
ActlysAI utilizes advanced machine learning and natural language processing algorithms for AI model building and deployment.
The process involves data integration, model selection, configuration, and deployment using intuitive steps.
Use cases for ActlysAI include customer service chatbots, predictive maintenance, and content generation.
No-code AI is democratizing access to AI, increasing efficiency, and unlocking new opportunities in various industries.
ActlysAI encourages users to join their community to explore the benefits of their innovative platform.

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Juris Framework: A Self-Testing Reactive Web Framework

Juris is a reactive web framework focused on fine-grained reactivity, component-based architecture, and state management.
It features a unique self-testing interface to validate the framework using its own capabilities.
Juris is built around six fundamental classes and avoids virtual DOM diffing in favor of precise updates.
The framework supports visual and headless components, a comprehensive testing framework, and 12 control flow components.
It allows object-to-DOM conversion, progressive enhancement of existing DOM elements, and has a non-destructive approach.
Juris includes a test runner with 9 UI components, tracks dependencies at the property level for optimal performance, and provides dependency injection.
The framework emphasizes testing, cleanup mechanisms, performance, and minimalist philosophy.
Juris is suitable for a wide range of applications and validates itself through rigorous self-testing.
Its comprehensive feature set, self-testing approach, and performance make it appealing for modern web development.

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Dev

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JurisKit: The No-Build Full-Stack JavaScript Framework That’s Redefining Developer Experience

JurisKit is an experimental framework challenging modern web development norms, focusing on fast developer feedback loops and performance.
It eliminates build steps and runs code as written, enabling instant changes with a refresh instead of long webpack processes.
Performance testing using Artillery showed JurisKit outperforming mainstream frameworks like Svelte, Vue/Vite, and Next.js.
JurisKit offers more functionality with less complexity and brings back straightforward debugging with direct code interpretation.
With minimal network requests and fast load times, JurisKit emphasizes developer velocity and simplicity over conventional tooling.
It presents a full-stack approach with universal components and headless architecture for routing, rendering, and state management.
JurisKit provokes questions about the necessity of build pipelines, the trade-off between convenience and velocity, and the impact of simplification on scalability.
As an experimental framework, JurisKit challenges web development norms by optimizing for performance and developer speed.
By reducing feedback loop times and enhancing server response speeds, JurisKit opens up new possibilities for web development.
While still in the experimental phase, JurisKit offers a fresh perspective on web development and highlights alternative approaches to building web applications.

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Dev

327

Post-Split Trauma: How to Debug Distributed Systems

Debugging a distributed system post-split introduces common failures like phantom writes, time travel bugs, cascading failures, silent data killers, and quantum entanglement bugs.
The article discusses solutions like idempotency keys, vector clocks, circuit breakers, checksum verification, and precise timing recording to address these issues.
It emphasizes using observability tools like Jaeger, ELK, and Prometheus for monitoring and provides a 3 AM playbook for troubleshooting distributed systems.
Prevention strategies include designing for failure, testing with Chaos Engineering, versioning contracts, and using feature flags.
Knowing when to revert to a monolith is recommended if debugging consumes excessive time or for transactions with strict latency requirements.
Start with basics like distributed tracing, implementing a circuit breaker, and conducting regular failure drills, even without being at Google's scale.

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The $100 Million Engineer: A Blueprint for Forging a Career in the New AI Gold Rush

In a mid-2025 podcast interview, Meta offers staggering sums, including $100 million signing bonuses, to poach top researchers from OpenAI in a strategic recruitment drive led by Mark Zuckerberg.
The aggressive recruitment strategy by Meta signals a shift in focus towards AI as its top priority, aiming not only to acquire talent but also weaken OpenAI by draining its resources.
Sam Altman criticizes Meta's cash-first culture, advocating for a mission-driven approach at OpenAI that fosters long-term innovation and loyalty.
The conflict between 'Culture vs. Capital' highlights the strategic choices facing aspiring engineers and the narrative of the AI talent war between Meta, OpenAI, and other tech giants.
The article outlines a four-phase roadmap for aspiring machine learning engineers, emphasizing foundational knowledge in mathematics and programming, mastery of Python libraries, predictive modeling, and advanced AI topics.
Building a strong portfolio of hands-on projects is crucial for aspiring engineers to demonstrate practical skills and stand out in the competitive machine learning field.
Kaggle competitions and structured project write-ups are recommended for beginners to showcase their problem-solving skills and storytelling abilities in their portfolios.
The article emphasizes the value of a well-documented GitHub profile and presenting projects in a clear and compelling manner to attract potential recruiters and hiring managers.
By systematically creating a diverse range of projects, aspiring engineers can prove their journey from novice to proficient practitioner, aligning with the demand for machine learning expertise in the global economy.
Ultimately, the AI talent war highlights the importance of deep skills, practical experience, and passion for innovation in building a sustainable and impactful career in the machine learning field.

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How to Set Up a Java Project with Gradle for Beginners

A Gradle project starts with the root folder where configuration files reside.
Creating the project folder and populating it with essential files like settings.gradle and build.gradle is essential.
Initiating a new Gradle project involves using 'gradle init' command in the terminal.
The generated layout includes build.gradle, settings.gradle, gradlew scripts, and gradle wrapper files.
Directories like src/main/java/ and src/test/java/ house main Java files and test classes respectively.
build.gradle file defines project behavior, including plugins, dependencies, and tasks.
Gradle automates tasks such as compiling Java files, running tests, and creating a JAR file using tasks defined in build.gradle.
Running Gradle commands like './gradlew build' compiles code, runs tests, and creates a JAR file in the build/libs directory.
Dependencies specified in build.gradle are automatically downloaded by Gradle and included in the compilation process.
Gradle simplifies project setup, management, and build processes by following defined structures and configurations.

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️ Flutter Code Push with Shorebird: Say Goodbye to Releasing a New App Every Time!

Shorebird Code Push is a real-time update system for Flutter apps that allows sending changes to Dart code directly to users' devices without republishing the app on stores.
It integrates a custom Flutter Engine into the app, enabling downloading and applying 'patches' to Dart code at runtime.
Shorebird offers seamless integration with CI/CD tools like Codemagic, GitHub Actions, and Fastlane for automation, reducing manual work and speeding up development cycles.
It supports Flavors (e.g., development, staging, production) and provides functionalities for releasing and uploading patches.
Shorebird does not affect native code, plugins, AndroidManifest.xml or Info.plist settings, and static assets.
It uses digital signatures, encryption for update protection, supports rollbacks, and offers precise control over targeted updates.
The integration process involves using PowerShell and commands to make changes, publish releases, and upload patches.
Shorebird aims to enhance productivity by minimizing the need for app republishing and accelerating the app development process.
Users can follow the guide to understand how to incorporate Shorebird Code Push into their Flutter workflow effectively.
The guide concludes with a note of gratitude for reading, encouraging sharing, comments, or questions.
Happy coding! 🚀

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