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Dev

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Unlock Cursor AI for FREE: 4 Secret Methods Revealed!

  • Cursor AI offers premium features for developers, but accessing them for free is possible through savvy techniques.
  • Maximizing Cursor's Free Tier provides ample functionality for personal projects and learning exercises.
  • Resetting the Pro Trial allows users to enjoy the 14-day premium features repeatedly using a time-bending approach.
  • Bypassing Membership Verification with the VIP tool offers a way to access Pro features without official verification.
  • Open-source solutions like the Identity Shifter and One-Command Solution provide additional workarounds.
  • While effective, these methods come with risks like account security vulnerabilities and potential violations of terms of service.
  • Users are advised to consider these techniques as temporary solutions and to weigh the value of Cursor's premium features against a paid subscription.
  • While professionals may benefit from a paid subscription for continued support and innovation, hobbyists and students can leverage free methods effectively.
  • Selecting the right approach among maximizing the free tier, extending trials, VIP bypass, or open-source solutions depends on individual needs and preferences.
  • Ultimately, balancing between free access and supporting developers through legitimate subscriptions ensures the tool's evolution and improvement.

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PlanetPython

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PyCon: Community Organizer Meet-up at PyCon US

  • A Community Organizer Meet-up will be held at PyCon US.
  • The purpose of the meet-up is to share experiences, challenges, and strategies in organizing Python and Python adjacent communities.
  • The meet-up will be a double Open Space session, aiming to initiate a more collaborative and purposeful era of Python community organizer knowledge sharing.
  • The Python Software Foundation (PSF) is exploring ways to support regular online communication and resource sharing among the Python community.

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Dev

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Enhancing Sales Data Visualization: Advanced Interactivity with CanvasJS and React Table

  • This article builds upon the foundation laid in my previous piece, 'Visualizing Sales Data with CanvasJS and React Table', where we explored the basics of setting up a sales dashboard using @tanstack/react-table and @canvasjs/react-charts.
  • Now, we'll take it a step further by diving into advanced interactive features—row highlighting in tables and dynamic tooltips in charts—to create a more engaging and user-friendly experience.
  • Features like row highlighting and interactive tooltips provide visual cues and additional context, making the data more accessible without overwhelming the user.
  • These enhancements will help users better navigate and analyze sales data, making the dashboard not just a display tool but an interactive exploration platform.

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Medium

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How AI Accelerates Software Development

  • AI is changing the game of software development by generating code snippets, functions, and even full backend endpoints from comments or prompts.
  • AI can identify and explain errors, suggest fixes, and even flag issues in code before it reaches the staging phase in the CI/CD pipeline.
  • AI tools help new developers understand the codebase quickly by providing answers to specific questions about functions and APIs.
  • AI can generate unit tests, suggest edge cases, and assist in working with legacy code by explaining cryptic functions and suggesting refactors.

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Fastify In-Depth: Speed, Performance, and Scalability Node.js Web Framework

  • Fastify is a high-performance Node.js web framework known for its speed, efficiency, and scalability.
  • It offers features like high performance, scalability, schema-based validation, logging with Pino, and TypeScript compatibility.
  • Fastify addresses performance and efficiency issues prevalent in older frameworks like Express and Koa.
  • The framework ensures high performance through efficient routing, precompiled serialization, schema-driven development, optimized plugin system, and low-cost abstractions.
  • Installation and usage examples with npm installation, route declaration, and server running are demonstrated.
  • Components like plugins, decorators, middleware, and hooks play vital roles in Fastify's flexibility and scalability.
  • Understanding the execution order and interruption capabilities of these components helps build efficient Fastify applications.
  • JSON Schema validation in Fastify ensures strict validation of request data formats and response structures.
  • Hooks are used to handle login statuses, limit parameters, and ensure request validation in Fastify applications.
  • Leapcell is recommended as a serverless web hosting platform for deploying Node.js services with support for multiple programming languages and pay-as-you-go pricing.

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Medium

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Vibe Coding: The Future of Programming or the End of Developers?

  • Vibe Coding is a new way of programming that involves guiding AI models to generate, refine, and debug code.
  • Developers can offload most of the work to AI, making software development a high-level direction process.
  • Using AI-assisted tools, Vibe Coding can quickly generate a Flask project with necessary components, such as a login authentication page.
  • Vibe Coding eliminates the need for deep dives into the codebase, allowing developers to rely on AI for automatic debugging.

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Medium

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Game-Changing React 19 Features You Need to Know.

  • The React Compiler is a new tool that transforms React components into optimized JavaScript code, automatically applying memoization and enhancing application performance.
  • React 19 introduces a new type of component that allows rendering separately on the web server, improving performance and enabling faster page loads.
  • The React compiler is currently in beta and under testing, not yet stable.
  • By caching UI directly on the server and minimizing client-side JavaScript, React 19 aims to achieve faster applications and improved SEO.

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Medium

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How to Detect Liquidity Grabs Using Divergence Logic in Pine Script (Without Getting Faked Out…

  • This article explains how to use divergence logic in Pine Script to detect liquidity grabs and avoid getting faked out.
  • The author suggests combining level sweeps with divergence indicators to identify potential liquidity grab zones.
  • By using tools such as RSI, OBV, MACD histogram, or volume, traders can find discrepancies between price and the chosen filter.
  • The technique helps traders avoid being tricked by fake breakouts and instead observe others getting caught in liquidity grabs.

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Medium

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Learning JavaScript Just Got Easier (Thanks to AI)

  • AI can assist in learning JavaScript by providing guidance, faster coding, bug fixing, and explanations in plain English.
  • Having a basic understanding of JavaScript is still essential to direct AI effectively in coding tasks.
  • Learning JavaScript today is more interactive and guided with the help of AI tools, reducing the learning curve.
  • With AI tools like ChatGPT, learners can receive clear answers and explanations, making the learning process less daunting.
  • AI tools have replaced traditional methods of seeking help, enabling learners to get targeted answers quickly.
  • Combining AI with JavaScript learning allows for immediate experimentation, enhancing understanding and problem-solving skills.
  • JavaScript's beginner-friendly nature, combined with AI assistance, offers a smooth learning experience.
  • With AI support, learners can receive code snippets and assistance in real-time, making coding tasks more efficient.
  • The article introduces a blog series inspired by the book 'Learn JavaScript Coding with AI,' focusing on JavaScript learning in an AI-powered world.
  • The series will cover essential JavaScript topics step by step, with practical examples and tips for real projects.

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Medium

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You’re Not the First: How Tech Stole Jobs & And How People Fought Back Through History

  • Machines replaced hand-made work in factories. People reacted by either destroying machines in protest or moved to cities for new jobs. Workers formed unions to demand fair pay.
  • Mass production and electricity reduced the need for skilled workers. Many moved to cities for factory jobs. Worker strikes and labor laws improved conditions. Some supported socialism, wanting workers to control businesses.
  • Computers and robots replaced jobs in offices and factories. Some lost jobs, but new ones appeared in IT and services. Governments started retraining programs, and people learned new skills.
  • AI and automation are replacing jobs in customer service, driving, and even creative work. Some worry about job losses, while others learn tech skills. Governments discuss Universal Basic Income (UBI) to support people if AI takes too many jobs.

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Dev

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Does AI really make you more productive?

  • In the 2024 Accelerate State of DevOps Report, it was found that 76% of developers are using AI tools in their daily tasks, though 40% have little trust in AI.
  • Some experienced developers feel less productive with AI-generated code, as it can be sloppy, complex, and prone to errors.
  • AI adoption negatively impacts software delivery performance, affecting both throughput and stability metrics.
  • AI-generated code often leads to larger pull requests, making reviews more challenging and potentially sacrificing throughput.
  • Code reviewers may overlook important details in large changes, impacting the efficiency of the review process.
  • AI-assisted code reviews may not be trusted if the code being reviewed is AI-generated, further complicating the stability of software changes.
  • Over-reliance on AI for code generation can create an illusion of speed, potentially compromising software quality and stability.
  • Increased AI adoption may lead to a perceived productivity increase, but could result in poorer quality software and more broken changes.
  • Vibe coding, dependent on AI for app development, can result in unstable applications, outages, security vulnerabilities, and loss of work.
  • Software development teams need to be cautious with AI adoption to prevent sacrificing stability for perceived productivity gains.

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Why you should learn multi-module architecture in compose as soon as possible!

  • Multi-module architecture is recommended for organizing an Android app effectively.
  • Building a production-grade app using a single-module architecture can lead to scalability and maintenance issues as the app grows.
  • Recommendation: Learn the fundamentals, explore architectural patterns, build small projects, and then transition to multi-module architecture for better scalability, maintainability, and performance.
  • Achievements: The author developed two applications using a multi-module architecture, which resulted in fewer bugs, easier scalability, and seamless feature additions.

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How to use FastAPI for microservices in Python

  • Microservices architecture involves decoupling functional parts into lightweight, deployable solutions adopted by leading companies like Netflix and Amazon.
  • Key features of microservices include standalone components, business-oriented structure, smart connections, decentralization, and resilience to failures.
  • API Gateways in microservices can impact response times, scalability, maintenance costs, and introduce potential points of failure.
  • Pros of microservices include independent services, modularity, easier feature additions, organized code base, and failure isolation.
  • FastAPI is a modern Python web framework for building APIs, known for code simplicity, high performance, and OpenAPI support.
  • Compared to Flask, FastAPI offers easier views declaration, data validation, JSON error messages, and asynchronous task support.
  • To install FastAPI, use pip to install 'fastapi' and 'uvicorn' packages to run the server for creating microservices.
  • Example microservice implementations using FastAPI include an authentication service and an information service for practical demonstration.
  • Microservices running together can be checked using curl commands, demonstrating authorization and successful service responses.
  • Microservices architecture is being widely adopted by tech giants and is likely to shape the future of backend software development.

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Javacodegeeks

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Building a Semantic Search System with Spring AI and PGVector

  • Semantic search enhances traditional keyword-based search by understanding the meaning and context of queries rather than relying on exact keyword matches.
  • The article discusses implementing semantic search using Spring AI and PGVector by integrating Ollama for generating embeddings that represent the semantic meaning of text.
  • Dependencies for the project include spring-ai-ollama-spring-boot-starter, spring-ai-pgvector-store-spring-boot-starter, spring-boot-docker-compose, and spring-ai-spring-boot-docker-compose.
  • Setting up the environment involves configuring Docker with PostgreSQL, PGVector, and Ollama, each serving specific purposes in the application.
  • Application properties are configured to interact with PGVector and Ollama, specifying settings for AI models, database connectivity, and Docker Compose integration.
  • A record class for movies is created to store movie data as embeddings in PGVector for semantic search, and a MovieStoragePipeline class handles the storage process.
  • The Semantic Search Controller processes user queries to find similar movie descriptions based on vector-based similarity search, enabling intuitive search experiences.
  • The application, once configured, automatically launches Docker containers and initializes the vector store to enable semantic searches based on textual queries.
  • Running queries like 'dystopian future' demonstrates the application's ability to perform semantic searches and retrieve conceptually matching documents.
  • In conclusion, the article showcases the integration of Spring AI, PGVector, and Ollama to build a semantic search system, empowering effective document retrieval with natural language processing capabilities.

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SPL: The Professional Choice for Processing Multi-Layered JSON Data

  • JSON’s nestable structure is ideal for representing hierarchical data relationships, such as orders containing customers and products with various details.
  • SQL lacks support for complex nested structures, while new databases like DuckDB offer partial support for processing JSON data.
  • DuckDB handles single-row nested fields efficiently but struggles with multi-row nested fields in calculations.
  • DuckDB can expand multi-row nested fields for calculations, which can be less efficient compared to using a physical flat table.
  • DuckDB can perform calculations on multi-row nested fields using lambda syntax, but this approach can be cumbersome.
  • esProc SPL fully implements multi-layer nested table mechanisms, providing concise and consistent code for data processing.
  • Python supports multi-layer nested structures but requires more complex coding compared to SPL, particularly for multi-row nested fields.
  • SPL offers concise and consistent syntax for handling nested data structures, making it a professional choice for such data processing tasks.
  • Python's syntax inconsistencies and verbosity in handling nested data make it less effective for complex calculations compared to SPL.
  • SPL simplifies the process of filtering and calculating data within multi-layer nested structures, offering clear and concise code.

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