Expressive, interactive data visualizations are the heroes of Observable Framework data apps. But behind the scenes are supporting software, tools, and architecture (like Node.js, npm, static site architecture, and data loaders) that play a key role in app performance and workflow flexibility. In our new blog post we demystify some unheralded essentials of building with Framework, so that data teams and analysts can more confidently jump into building best-in-class data apps:
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If you are looking to build rich and robust data visualization apps, check out these essentials Allison Horst, PhD #DataVisualization #DataFam #DataAnalysis
Expressive, interactive data visualizations are the heroes of Observable Framework data apps. But behind the scenes are supporting software, tools, and architecture (like Node.js, npm, static site architecture, and data loaders) that play a key role in app performance and workflow flexibility. In our new blog post we demystify some unheralded essentials of building with Framework, so that data teams and analysts can more confidently jump into building best-in-class data apps:
Unheralded essentials of Framework data apps: an overview for data teams
observablehq.com
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So, an R data scientist walks into a JavaScript bar... I wrote this short primer with data scientists (like me!) in mind, with the aim of demystifying some unheralded essentials of building data apps with Framework. These are things that'll be familiar to JavaScript developers, but perhaps new to data teams & analysts working primarily in Python, R, SQL, etc. Also got an Inigo Montoya quote through review 🗡 Check it out!
Expressive, interactive data visualizations are the heroes of Observable Framework data apps. But behind the scenes are supporting software, tools, and architecture (like Node.js, npm, static site architecture, and data loaders) that play a key role in app performance and workflow flexibility. In our new blog post we demystify some unheralded essentials of building with Framework, so that data teams and analysts can more confidently jump into building best-in-class data apps:
Unheralded essentials of Framework data apps: an overview for data teams
observablehq.com
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🔄 Handling Asynchronous Data in React: Challenges You Might Face As developers, we all know how complex handling asynchronous data can be. In React, the process often involves dealing with various states like loading, success, error, and empty data. These states can quickly become repetitive and result in messy, inconsistent code. Here are some common challenges when working with async data in React: . Managing Multiple Loading States: Whether fetching data for a list, individual item, or details view, handling different loading indicators can get out of hand. . Error Handling: Displaying error messages in a user-friendly way can be tricky, especially when users need an option to retry the request. . Empty Data Handling: How do you gracefully handle empty data or no results found without making the UI look incomplete? . UI Consistency: Maintaining a consistent user interface across different states while keeping the codebase clean and maintainable can be a major hurdle. 🎯 But don't worry! I’ve tackled these challenges with a powerful solution using React Query and a flexible, reusable component that simplifies the handling of asynchronous states. 🚀 If you're facing similar struggles, check out my latest blog post where I walk through the entire process of building a MatchQueryStatus component for seamless async data handling. https://lnkd.in/d8BWdUSs #React #ReactQuery #AsyncData #CodeSimplification #SoftwareDevelopment #WebDevelopment
Building a Flexible MatchQueryStatus Component for Handling Async Data in React
hasseebmayo.com
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There has been a notable increase in data visualization projects at Marzee, and we are having a blast working on these projects. I wrote an article with a few of the benefits we see in using #reactjs for #datavisualization interfaces 🤘
🚀 Our latest newsletter is out, featuring an article on the critical role of data visualization in today's data-driven world and why React is an outstanding tool for building dynamic data visualization interfaces. We dive into the benefits of using React for real-time, interactive dashboards, highlighting its rich ecosystem, component-based architecture, and powerful performance optimizations. Discover how React can help you create modern, engaging, and efficient data visualization applications, whether you're developing dashboards, data analysis tools, or interactive reports. #DataVisualization #ReactJS #FrontendDevelopment #BigData #DataDriven #JavaScript #WebDevelopment #TechNews #Newsletter #MarzeeTech https://lnkd.in/dPhTfA_v
10 Benefits of Using React for Data Visualization Interfaces
marzee.substack.com
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🚀 Our latest newsletter is out, featuring an article on the critical role of data visualization in today's data-driven world and why React is an outstanding tool for building dynamic data visualization interfaces. We dive into the benefits of using React for real-time, interactive dashboards, highlighting its rich ecosystem, component-based architecture, and powerful performance optimizations. Discover how React can help you create modern, engaging, and efficient data visualization applications, whether you're developing dashboards, data analysis tools, or interactive reports. #DataVisualization #ReactJS #FrontendDevelopment #BigData #DataDriven #JavaScript #WebDevelopment #TechNews #Newsletter #MarzeeTech https://lnkd.in/dPhTfA_v
10 Benefits of Using React for Data Visualization Interfaces
marzee.substack.com
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⚙️ Mastering the Event Loop in Node.js: The Power of process.nextTick! If you're a backend developer working with Node.js, you've likely encountered the infamous event loop. Understanding how to control its behavior can be a game-changer for writing efficient and bug-free code. One essential tool for this is process.nextTick. But what does it do, why is it important, and when should you use it? Let’s break it down! 🛠️ 📄 What is process.nextTick? In Node.js, process.nextTick allows you to schedule a callback to be executed immediately after the current operation completes, before any I/O or timers are processed. Even though process.nextTick is asynchronous, it always runs before any I/O events or timers. 💡 Why is it Important? 1️⃣ Prioritizing Critical Tasks: Sometimes, you need to ensure a task runs as soon as possible after the current operation without waiting for the I/O cycle. 2️⃣ Avoiding Stack Overflow: When performing recursive operations, using process.nextTick prevents deep call stacks by deferring execution. 3️⃣ Compatibility and Polyfills: It’s useful when creating libraries that need to mimic synchronous behavior while still operating asynchronously. 📚 Here's a quick snippet to get you started: 1️⃣ Creating the Stream: CustomStream extends Node.js's Readable stream, allowing us to implement the _read method. _read is called by the stream whenever it needs more data. Here, we simulate data chunks with an array (['chunk1', 'chunk2', 'chunk3']). 2️⃣ The _read Method: If there’s data left in the array, we shift (remove) the next chunk from the array. Instead of pushing the chunk immediately, we use process.nextTick to defer the this.push(chunk) call until the next iteration of the event loop. If there’s no data left, we call this.push(null) to signal the end of the stream. 3️⃣ Consuming the Stream: The 'data' event is triggered each time a chunk is pushed. The 'end' event is triggered when the stream signals it has no more data (this.push(null)). 🤔 But why Use process.nextTick Here? Without process.nextTick, the this.push(chunk) call would happen synchronously. This means the 'data' event would fire immediately, potentially before the consumer has had time to set up its event handlers or process the previous chunk. Visualizing the Event Loop: Here’s how it plays out with process.nextTick: 1️⃣ _read is called, and a chunk is prepared (chunk1 is shifted from the array). 2️⃣ Instead of immediately emitting the 'data' event, process.nextTick schedules the this.push(chunk) for the next tick. 3️⃣ The event loop continues to process other tasks before executing the 'data' event. 4️⃣ This cycle repeats for subsequent chunks (chunk2, chunk3) until the stream ends. **credits to Erick Wendel and his excellent "JS Expert" course. #JavaScript #DesignPatterns #FrontendDevelopment #WebDevelopment #DeveloperLife #nodejs #backend #backenddeveloper #Nestjs
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Mastering React Hooks: Understanding Types and Uses ⚛️✨ React Hooks are powerful tools that enable functional components to manage state and side effects without needing class components. They simplify how we interact with React’s features and help us write more concise, maintainable code. Let’s break down the key types of React Hooks and their uses! 1. useState Use: The useState hook allows you to add state to functional components. It’s used to store and update values that change over time, such as user inputs, counters, or toggle states. When to Use: Use it when you need to track any dynamic data within your component, like a counter, form input, or UI visibility state. 2. useEffect Use: The useEffect hook handles side effects in functional components, such as fetching data, subscribing to a service, or manually manipulating the DOM. It runs after every render by default but can be customized to run conditionally. When to Use: Use useEffect for actions like making API calls, handling events, or updating external systems based on state or props. 3. useContext Use: The useContext hook allows you to access global state or shared data across multiple components, without needing to pass props down through every level. When to Use: Use it for managing app-wide state like themes, authentication, or settings that need to be accessed by many components. 4. useReducer Use: The useReducer hook is an alternative to useState and is ideal for managing more complex state logic, especially when the state involves multiple sub-values or complex transitions. When to Use: Use it for more sophisticated state management needs, such as handling multiple state updates based on actions (e.g., forms with many fields or applications with intricate state logic). 5. useRef Use: The useRef hook is used to persist values across renders and access DOM elements directly. It can store mutable values that don’t trigger re-renders when changed. When to Use: Use it to reference DOM elements (e.g., for focus control), store interval timers, or keep any values you want to persist without causing a re-render. 6. useMemo Use: The useMemo hook is used to memoize expensive calculations and prevent unnecessary re-computations. It only recalculates the value when its dependencies change. When to Use: Use it when you have computationally expensive operations that should only re-run when certain dependencies change, optimizing performance. 7. useCallback Use: The useCallback hook returns a memoized version of a callback function, preventing unnecessary re-creations of the function on every render. When to Use: Use it when passing callbacks to child components, especially when these functions are used in useEffect or passed down as props, to prevent unnecessary renders. #React #ReactHooks #WebDevelopment #JavaScript #FrontendDevelopment #useState #useEffect #useContext #useReducer #useMemo #useCallback
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Best Free React DataGrids to Use in 2025 - DEV Community: Data grids, in particular, play a crucial role in web applications by allowing developers to efficiently display, sort, filter, and manipulate large ... #bigdata #cdo #cto
Best Free React DataGrids to Use in 2025
dev.to
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"With the growing complexity of financial markets, effective data visualization can make the difference between identifying trends and missing opportunities." An article explores how React has become a cornerstone of data visualization for financial markets due to its simplicity, modularity, and performance. Create a variety of charts and manage big data sets in real time, with ease ... "As financial markets continue to grow in complexity, the importance of effective data visualization cannot be overstated." Read more at the link. #React #Javascript #financialdata #financialcharts #chartlibrary #decisionscience #industrynews #datavisualization
Visualizing Financial Data Using React Charts and JavaScript
msn.com
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Laravel developers, looking to streamline your data processing workflows? Dive into Laravel's powerful Pipeline pattern! 💎 This elegant feature allows you to pass data through a series of operations, perfect for complex processes like order processing or user registration. By leveraging the Pipeline pattern, you can create more modular, maintainable, and testable code. #Laravel Curious about how to implement this pattern in your Laravel projects? Check out the full blog post:
Streamlining Data Processing with Laravel's Pipeline Pattern
harrisrafto.eu
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