clean architecture

An over engineered Todo app I use to teach myself Clean Architecture in Rust.

Backend для веб-приложения Expense Tracker.

Приложение для бюджетирования расходов, заточенное под путешественников.

Multiplatform SDK for creating clients on various platforms (Android, iOS and browser)

personal ecommerce for scalling learning and apply good practices based on clean architecture and domain driven design

RabbitMQ se trata simplemente de un software que es utilizado para la gestión de envíos de mensajería haciendo uso de un protocolo de base conocido como Message-Broker.

Solución que contiene cuatro proyectos y que hace uso de la Arquitectura Limpia utilizando CQRS.

En la Parte dos hemos visto un sencillo ejemplo aplicado sobre una arquitectura Monolítica. En esta ocasión veremos cómo implementarlo en una arquitectura basada en Microservicios. En este caso particular voy a describir algunas de las etapas más importantes y algunos de los cambios en comparación con la arquitectura Monolítica.

Ejemplo basado en el uso combinado de PostgreSQL y Redis, haciendo uso del patrón CQRS (Command Query Responsability Segregation), bajo una arquitectura limpia (Clean Architecture) sobre una arquitectura monolítica.

ASP.NET Core APIs for an advanced online hotel booking system. Including the Login Page, Home Page, Search Results, Hotel Details, Secure Checkout, and Admin Management.

An example project shows DDD and Clean Architecture usage.

CleanArchMvc é um projeto feito para demonstrar a implementação de uma arquitetura limpa (clean architecture) em uma aplicação web ASP.NET Core MVC

CVR Official App. Developed to be posted on google play.

Hexagonal Architecture vs Onion Architecture vs Clean Architecture vs Layered Architecture vs Component-Based Architecture

API using the Go programming language, following the Clean Architecture

The project is a real estate and car property management system. The core idea is to facilitate property buying and selling, eliminating the need for real estate offices.

The system incorporates the following key features:

Users can't access the system without confirming their identity and account, ensuring the credibility of users by obtaining essential data. The system is divided to ease usability, with dedicated sections for property (houses and lands) and cars, facilitating user search. To counter fake data, we employed Artificial Intelligence and Machine Learning; any images not depicting real estate or cars are automatically removed. We utilized Google Maps for precise user location. For data browsing in the property and car sections, we implemented pagination to retrieve data from the server in batches, enhancing user experience. Advanced filtering and search capabilities are available. Real-time communication is facilitated through in-system chat or direct calls using mobile numbers. Data retrieval isn't random; it returns favorites and similar items for the user, along with the highest-rated properties. Users can rate properties, add them to favorites, and view the number of likes for each post. In-app notifications for messages and likes are present. Each user has a personal profile to manage favorites and posts; sellers can delete their posts after selling. Users can modify their data. Password recovery is enabled via Gmail verification code. The system supports both Arabic and English languages. Account deletion is possible.

Project untuk codebase RESTFull API menggunakan bahasa Golang.