Best of Medium — June 2024

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    Airclap — Send any file to any device

    Airclap is a cross-platform file transfer tool that enables users to easily share any file type across devices like iOS, macOS, Android, Windows, and Linux. With a minimalist design, it offers secure and high-speed transfers using AES encryption and a customized SSDP discovery protocol. Key features include one-step file transfer, offline sending, and integration with over 20 languages. It supports numerous use cases ranging from developer workflows to educational resource sharing. Airclap is permanently free and does not require an internet connection, ensuring user data privacy.

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    I spent 18 months rebuilding my algorithmic trading platform in Rust. I’m filled with regret.

    An experienced developer reflects on his 18-month journey rebuilding an algorithmic trading platform in Rust, expressing profound disappointment. Despite Rust's reputation for speed and safety, the author found its syntax and error handling to be horrendous, leading to significant frustration and regret. Additionally, the Rust community's unhelpful attitude compounded the difficulties. Ultimately, while Rust has its merits, the author suggests that languages like Go may offer a better balance of speed and ease of development.

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    Roadmap to Learn Data Engineering: How I Would Start Again

    A roadmap for learning data engineering, covering Python, SQL, command line, data warehouse, data modeling, data storage, data processing, data transformation, data orchestration, advanced topics, and staying updated.

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    Building an AI Text-to-Video Model from Scratch Using Python

    This post discusses building an AI text-to-video model from scratch using Python. It covers the GAN architecture, understanding GANs, the training process, and generating AI videos based on text prompts.

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    React Projects and State management

    Learn about the useState hook in React, its usage in applications, and best practices for using it. Discover how the useState hook can help manage and update data in your projects.

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    Did Google Just Kill Streamlit?

    Google's new open-source Python framework, Mesop, aims to facilitate rapid prototyping and internal tooling, similar to Streamlit. Mesop is still in its early stages and is not officially supported by Google. It offers features like idiomatic Python coding, hot-reloading, and component-based architecture built on Angular. Unlike Streamlit, deploying a Mesop application requires containerization. Streamlit remains robust, especially for data visualization projects, but Mesop shows promise for quick, customizable prototypes.

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    10 Best Practices for Data Science

    This post discusses 10 best practices for data science, including starting and staying organized, using version control, separating notebooks and source files, writing tests and sanity checks, automating the data pipeline, centralizing important parameters, making project runs verbose, and starting with a simple end-to-end pipeline. These practices promote reproducibility, collaboration, reliability, and efficiency in data science projects.

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    I tried React Compiler today, and guess what… 😉

    The article explores the use of React Compiler, a tool developed by the React core team, to solve the problem of unnecessary re-renders in React components. It discusses the installation process, provides examples of using React Compiler, and evaluates its effectiveness in real-world scenarios. The author concludes that while React Compiler can improve performance in some cases, manual memoization techniques such as React.memo, useMemo, and useCallback are still necessary to optimize component rendering.

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    Linear Algebra Concepts Every Data Scientist Should Know

    Linear algebra is fundamental in transforming theoretical data science models into practical solutions. It is crucial for data representation, dimensionality reduction, optimization, feature engineering, and similarity measures. Concepts such as vectors, vector spaces, matrices, and operations like dot products and matrix multiplication are key foundational topics. Understanding the basis, rank, determinants, eigenvectors, and eigenvalues are vital for advanced applications in data science and machine learning.

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    Kotlin MultiPlatform (KMP)

    Learn about setting up the environment for Kotlin MultiPlatform development, the structure of a KMM project, and using coroutines in iOS.

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    Understanding the Virtual DOM Structure in React

    Understanding the Virtual DOM Structure in React. Exploring the concept of Virtual DOM and Fiber Nodes in React, and how React Fiber works to manage UI updates efficiently.

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    101 Things I Never Knew About Python

    The post shares insights from an experienced Python developer who has written extensively on the language. It details the author's journey from learning Python in university to becoming a full-stack software engineer and prolific writer on Medium. The post also introduces a book compiled from over 700 articles, aiming to consolidate various Python tricks and concepts learned over the years.

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    The Internet isn’t Fun Anymore

    The Internet used to be a safe space for exploring and connecting, but now it feels suffocating due to constant AI tools, ads, and monetization. Users have limited agency and feel overexposed. Companies are pushing AI features that are often annoying or useless. Some companies are marketing active refusal of AI. People are losing their ability to make choices and think for themselves online.

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    Kotlin Lazy vs Lateinit Explained

    The post explains the differences between lazy and lateinit property initializers in Kotlin. Lazy initialization is used for immutable properties (val), ensuring they are initialized when first accessed, which can help with resource management. Lateinit is used for mutable properties (var) and must be initialized before use to avoid runtime exceptions. The post also discusses when to use these initializers, provides code examples, and touches on advanced concepts like using delegates for primitive types.

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    10 Software Engineering Lessons from Transforming our Appointment Search

    The post shares 10 essential software engineering lessons learned from developing an advanced appointment search system at Doctolib. Key insights include understanding legacy code via product questions, using multiple caching strategies, maintaining high cohesion and low coupling in code, avoiding circular dependencies, and utilizing various release strategies. These lessons aim to improve project implementation, debugging processes, and overall software performance.

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    Forecasting Gold Prices with TimeGPT

    This post explores how TimeGPT, a time series LLM model, can be used with gold price data to accurately forecast future prices. The post covers the process of retrieving gold price data, preprocessing the data, setting up TimeGPT, and interpreting the forecasted prices and confidence intervals.

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    Multi AI Agent Systems 101

    This article explores the use of multi-agent systems in automating routine tasks in data source management. It discusses the benefits and drawbacks of using AI agents, as well as popular frameworks for building multi-agent systems. The article also provides a step-by-step guide on using the CrewAI framework for automated documentation and answering questions based on the documentation.

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    What would happen to FlutterFlow if Google stops funding Flutter?

    FlutterFlow users shouldn't be worried if Google stops funding Flutter because Google has provided significant support to Flutter, Flutter has a strong community and corporate adoption, and Flutter is open source and has diverse contributors. If necessary, FlutterFlow can pivot to using other technologies.

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    Ace the Netflix Interview: Must-Know Python Coding Problems

    Learn how to tackle coding problems like a member of the Netflix dream team using the Modified Binary Search pattern and other important patterns. Mastering these patterns will help you excel in your technical interview at Netflix.

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    Best Firebase Tools for Your Mobile Application

    Building mobile applications can be challenging, especially for startups with limited resources. Firebase offers a comprehensive suite of tools that simplify tasks such as authentication, push notifications, real-time databases, and more. These tools allow developers to focus on core product features rather than backend infrastructure. Firebase's no-cost plan makes it an attractive option for enhancing services without high costs. Its features include easy integration for authentication, efficient push notification systems, real-time data synchronization, app distribution, crash reporting, and performance monitoring.

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    Common mistakes with Images in Flutter

    Learn about common mistakes with images in Flutter, such as using large image assets, not using WebP assets, and using the Opacity widget unnecessarily.

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    Powering Angular with Rust (Wasm)

    This post explains how to set up and start using Rust in an Angular application. It discusses the benefits of using WebAssembly for performance-intensive tasks and provides a step-by-step guide to creating a Rust library for an Angular app.

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    How to Maximize Your Impact as a Data Scientist

    Learn why focusing on impact is important for data scientists' career growth, the challenges in driving real impact, and how to become more impact-focused in your work.

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    I Found 21 Platforms to Sell AI Art and Make Passive Income

    Discover 21 platforms to sell AI art and generate passive income. Explore popular platforms like Etsy, Redbubble, Society6, Zazzle, and more. Find out how to start selling and make money from AI-generated images.

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    How to Setup Automatic Versioning for your FastAPI App

    Learn how to set up automatic versioning for your FastAPI applications using semantic versioning, Git commit messages, and the python-semantic-release package. This guide explains the importance of versioning, the basics of semantic versioning, and provides a step-by-step process to install and configure python-semantic-release, including integrating it with GitHub Actions for continuous integration.

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