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TypeScript Generics Propagation in useOptimistic react hook

Generics in TypeScript facilitate reusable, type-safe code by parameterizing types and ensuring correct application of these types in various contexts, such as React components like the useOptimistic hook.
TypeScript generics, like , specify generic types for functions or classes, allowing for type-safe operations with different data types.
TypeScript's type inference can often eliminate the need for explicit generic annotations, inferring types from contextual information.
The useOptimistic hook example showcases the usage of generics for managing state and data updates in a user-friendly way.
By simplifying generic signatures using T and A as placeholders, the code becomes more concise and readable.
Generics propagation ensures consistency in type application through function calls, object manipulations, and component interfaces, promoting type safety in various contexts.
For components like useOptimistic, generics propagation guarantees the correct typing of state, actions, and updates throughout the component lifecycle.
Understanding TypeScript generics propagation leads to writing more maintainable, type-safe code and leveraging TypeScript's type checking capabilities.
Complex generic constraints and incorrect type assumptions are common pitfalls to avoid when utilizing generics in TypeScript.
Simplifying generic usage and leveraging TypeScript's type inference can enhance code readability while preserving type safety.

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Dev

223

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Please help me!

The article addresses a JavaScript error: Uncaught SyntaxError: expected expression, got ')', which occurs in the main.js file at line 1032.
The code consists of various sections, including the initialization of global data objects and modules such as Modal Control, Schedule Interactions, Qualification Matrix Interaction, Employee Edit/Delete Logic, and Machine & Group Edit/Delete Logic.
The code dynamically loads data from the API, populates form fields, handles modal interactions, and includes event listeners for editing/deleting employees, qualifications, machines, and groups.
It also implements features like opening modals, filling form fields, submitting form data via API calls, handling click events, and updating table data upon successful actions.
The script defines functions for processing form submissions, updating schedule cells, managing qualifications, editing/deleting employees, and machines or groups.
It demonstrates best practices such as event delegation, dynamic form population, error handling, and visual feedback for user interactions.
The code is structured to handle different types of interactions and includes error logging and alerts for user feedback.

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Medium

278

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How Dev Containers Made My Development Environment Effortless

Dev Containers allow for multiple development configurations without collision problems or compatibility issues.
Dev Containers make it easier to work with different versions of SDKs, such as Java, Python, and Ruby.
Dev Containers offer portability for development environments, enabling the ability to work on projects from different machines.
Dev Containers provide a hassle-free way to set up a development environment and manage multiple configurations.

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16 Likes

Medium

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Go Gopher base form: Foundations of the language

Go Gopher base form: Foundations of the language
A Go project consists of Go packages and a go.mod file.
Packages in Go define the structure of the code.
Importing packages can be done locally or externally.

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Dev

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A critical look at the modern programming landscape

The modern programming landscape is evolving rapidly, influenced by languages like Lisp, Smalltalk, io, and Unison.
Current development in programming seems confined to a space limited by past abstractions, prompting a call for revolutionary progress over evolutionary changes.
Challenges with managing state in programming, the complexities of distributed programming, distributed state, concurrency, tree structures, and text files are analyzed.
Issues like global vs. local state handling, distributed system design, stack-based concurrency control, and the limitations of file systems as abstractions are discussed.
Advocacy for languages to facilitate better state management, seamless remote function calls, and deeper integration with IDEs for enhanced programming experiences is highlighted.
The need for languages to support clear expression of state, simplify distributed programming, and enable meaningful diffs and sharing of objects is emphasized.
Proposals for improving concurrency, leveraging tree structures to model complex relationships, and bypassing text-to-binary transitions in programming are put forth.
The article concludes by urging the programming community to consider ambitious ideas that may have been ahead of their time and push for a new generation of programming languages.

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Dev

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What I learned from Vibe Coding

Vibe coding is a new approach in software development that leverages AI for code writing, resulting in increased productivity and faster completion of tasks.
Developers using AI can achieve efficiency gains and benefit from AI-driven code debugging, commenting, and refactoring.
Vibe coding involves focusing on high-level concepts, letting AI generate implementation details, and accepting AI suggestions with minimal review.
Cursor AI is an AI-powered code editor that enhances coding experience by assisting with tasks like code completion, generation, and understanding codebase.
Setting up Cursor involves keybinding configuration, choosing prompting language, and granting access to the full code to maximize its effectiveness.
Vibe coding with Cursor involves steps like project planning, guideline setting, writing prompts, reviewing output, and iterating through AI assistance.
AI tools like Cursor can generate code, fix issues, integrate frontend with backend, create unit tests, and prepare applications for deployment.
The future of software development with AI tools may involve a merge of roles, demand for proficiency in multiple languages, and a continuous learning process.
Efficient use of AI tools will provide a competitive advantage in the evolving landscape of software development, emphasizing the importance of continuous learning.
Despite advancements, manual intervention in software development will remain essential due to the evolving nature of AI technologies.

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Logrocket

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What is glassmorphism? How to create glassmorphic designs

Glassmorphism is a UI design trend that leverages glass-textured backgrounds to create a modern or futuristic aesthetic, suitable for luxury brands and tech products.
Pros of glassmorphism include being clean, modern, engaging, easy to design and code, performant, and helpful in establishing visual hierarchy.
Cons of glassmorphism include potentially making apps or websites look cluttered and posing challenges with color contrasting for optimal accessibility.
Originating in Windows Vista and refined by Apple in iOS 7, glassmorphism has gained popularity but is often showcased more in designs than in real products.
Creating glassmorphic designs involves properties like opacity, background color, background blur, border, drop shadow, and gradient to impact user experience.
Glassmorphism can be practical to implement on the web and in apps, with modern CSS features making it easier than before.
Best practices for glassmorphism include ensuring accessibility, keeping the effects subtle, and using it thoughtfully for a luxury or tech brand.
While glassmorphism can be visually appealing and attention-seeking, it should be used sparingly and with consideration for usability and accessibility.
Microsoft and Apple have showcased the potential of glassmorphism, but its widespread adoption in real products remains limited despite being a popular design trend.
Despite the initial complexity, modern advancements make implementing glassmorphic effects into production apps and websites easier.
In conclusion, glassmorphism can be a good UI design trend to follow when used judiciously, balancing visual aesthetics with usability and accessibility considerations.

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Dev

287

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Refactoring 027 - Remove Getters

The article discusses the importance of removing or replacing getters with behavior-rich methods in object-oriented programming.
By removing getters, the code can address issues like anemic objects, excessive coupling, lost encapsulation, and violations of the Law of Demeter.
Steps provided include identifying getters, moving behavior into objects, and creating intention-revealing methods.
Sample code demonstrates the transformation from using getters to method-based behavior in an Invoice class.
The refactoring aims to centralize logic within objects, hide implementation details, reduce coupling, and prevent violations of design principles.
Removing getters helps objects behave more like real-world entities, strengthening the correspondence between code and reality.
Limitations include challenges in dealing with frameworks expecting getters and difficulties in refactoring legacy codebases.
The refactoring process involves finding, moving, and updating code to use new methods as behavior-rich alternatives to getters.
It's an intermediate level refactoring that improves code quality and aligns better with object-oriented principles.
Related refactorings include removing setters, extracting methods, and protecting public attributes.
The article also suggests using the MAPPER principle and AI tools for effective refactoring.

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Mjtsai

Investigating MacPaint’s Source Code

The source code of MacPaint, one of the launch applications for the Apple Macintosh in 1984, is being investigated.
The design and implementation of MacPaint are examined, focusing on buffer management and bucket filling algorithms.
Positive and negative aspects of the code style and architecture are identified, along with its pliability for change.
MacPaint's significance and impact on the development of digital graphic systems are emphasized.

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Dev

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I Built My First React App: A Beginner's Walkthrough of a Simple To-Do App.

I'm currently on a 6-month journey aiming to become a job-ready cross-platform app developer.
The author built their first React app - a simple To-Do List, and shared their learning experience as a complete beginner.
The app uses React, JSX, useState, basic HTML/CSS, and implements key concepts like components, state management, event handling, rendering lists, and conditional rendering.
The author plans to continue learning React Router, APIs, and React Native to build mobile apps.

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Dev

329

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Post 5: 🚀 From Slow Load to Lightning Speed: Quantifying Our React Performance Wins!

We achieved an approximate ~70% reduction in page load time, leading to lower bounce rates, increased conversion rates, and happier users.
Our React build time has been reduced by approximately 80%, resulting in faster iteration cycles, more frequent deployments, and more productive developers.
Key tools and technologies used include CRACO, webpack, and React's lazy loading.
The performance optimization efforts have resulted in a faster and more efficient app for users and developers.

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19 Likes

Dev

396

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Crafting Killer Accuracy Metrics for AI Apps

Accuracy metrics are crucial for evaluating AI apps, offering insights into model performance.
In the context of AI that extracts API endpoints, key metrics include True Positives (TP), False Positives (FP), False Negatives (FN), and True Negatives (TN).
Precision measures the accuracy of flagged endpoints, while recall indicates how many real endpoints were captured.
The F1-score balances precision and recall, providing a comprehensive metric for model performance.
Creating accuracy metrics involves defining goals, setting up test sets, computing metrics with tools like scikit-learn, and handling trade-offs.
Various scenarios demonstrate the impact of adjusting AI strictness on precision and recall trade-offs.
It's essential to address pitfalls like imbalanced data, metric obsession, and considering the context when prioritizing precision or recall.
Additional metrics like Accuracy, AUC-ROC, and mAP offer different perspectives on model evaluation.
Crafting accuracy metrics empowers AI developers to understand and optimize their models effectively.
The guide provides a step-by-step approach, combining practical examples, technical insights, and the fishing analogy to enhance comprehension.
Navigating the intricacies of accuracy metrics enables AI practitioners to fine-tune their models for optimal performance.

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23 Likes

Medium

303

Introducing Trae: The AI-Powered Code Editor That’s Redefining Development

Introducing Trae: The AI-Powered Code Editor That’s Redefining Development
Trae is a modern IDE built upon Visual Studio Code, integrating advanced AI capabilities into the development workflow.
Key features include intelligent code completion, conversational programming, builder mode, and multi-language support.
Trae offers real-world applications such as rapid prototyping, code refactoring, learning and onboarding, and debugging assistance.

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18 Likes

Dev

325

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Build Your Own Podcast Producer AI Agent🎙️

This article discusses how to build an AI News Podcast Producer Agent using the Supercog Agentic Framework.
Installation options are provided for setting up the agent, and API keys are required to use the Podcast Agent.
The agent utilizes multiple AI models and tools to generate, narrate, and publish daily news updates on AI, Sports, and Finance.
The article concludes by highlighting the capabilities of the Supercog Agentic Framework and providing relevant resources for further exploration.

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Dev

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Post 4: Caching and Cache Busting - Ensuring a Smooth User Experience:

Browser caching stores static assets locally for faster load times on return visits, enhancing user experience.
Cache busting techniques ensure that updated static assets are fetched by the browser to prevent display inconsistencies.
Filename hashing, incorporating hash into file names, is a widely used cache busting strategy to trigger updates when content changes.
Incorporating hashing into chunk names using webpack configuration, like [contenthash:8], automates cache busting for content updates.
Other cache busting techniques include versioning by adding version numbers to asset URLs and using query parameters.
Project implemented filename hashing to address chunk loading errors, ensuring users receive the correct code version consistently.
Strategies like retry mechanisms and fallback UI help handle chunk loading errors gracefully and maintain application resilience.
Combining caching and cache busting optimizes performance by ensuring fast initial load times and up-to-date content for users.
Implementing these techniques effectively enhances user satisfaction and creates a seamless user experience.
Browser caching boosts speed for repeat visits, while cache busting ensures users receive the latest updates, with filename hashing being a robust technique.

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