Test-driven development (TDD) has become an essential approach in modern software engineering. It not only helps developers write cleaner code but also ensures that the application is well-tested from the start. In this guide, we’ll explore how to apply TDD in a React project using Jest and React Testing Library. By the end, you’ll see the benefits of adopting TDD in your development process.

Imagine this: One day, you’re deep in the trenches, your fingers dancing across the keyboard, every keystroke bringing your ideas to life. The next day, you’re handed the captain’s hat, expected to steer the ship, chart the course, and keep the crew motivated — all while still keeping your coding skills sharp. It’s like going from being the star player to the coach overnight. This is my story — my first year as a tech lead, where I learned that leading a team isn’t just about writing the perfect line of code but crafting the blueprint for success.

Welcome to Part 2 of adding input validation in Go! In the previous part, we covered the basics of validating user input in Go using Fiber and go-playground/validator. We noticed that our code was getting a bit messy with all the validation checks, making it harder to manage. In this installment, we’re going to tidy things up. If you haven’t read Part 1 yet, we suggest giving it a quick look to get up to speed. In this part, we’ll show you how to clean up and optimise our validation code, making it easier to read and maintain. Let’s get started!

Data validation is like checking if the keys fit before opening a door. It ensures that the information we get from users is safe and correct. Without it, our websites could become vulnerable to sneaky attacks from hackers. In this blog, we’ll learn how to easily check and handle the information users give us using Go with Fiber and a tool called go-playground/validator.

In modern development, React and Typescript are powerful combinations that can help you build robust, maintainable, and scalable applications. To leverage these technologies effectively, understanding various design patterns is essential. In this blog post, we’ll dive into some common design patterns used in React with Typescript, complete with real-world examples.

React refs are a powerful feature that allows you to directly interact with DOM elements and React components. This blog will explore why and when to use refs, the different ways to use them, how to access functional component methods using refs, and additional tips for using refs effectively.

When it comes to styling web pages with CSS, understanding the different units of measurement is crucial. Three common units are px , em , and rem . Each has its unique characteristics and use cases. This blog will explore these units with practical examples to help you understand when and how to use them effectively.

React is a powerful Javascript library for building user interfaces. One of the key concepts in React is the component lifecycle. Understanding this lifecycle is essential for building robust and efficient components. In this blog post, we’ll explore the lifecycle of React components, both in <strong>class-based</strong> and <strong>functional</strong> components.

In our previous <a href="https://medium.com/@savan.chhayani/efficient-order-organization-with-javascript-unleash-the-power-of-map-filter-and-reduce-c924c9a3b05c">blog</a>, we embarked on a journey to explore the practical applications of JavaScript’s most indispensable functions: map, filter, and reduce. However, beyond their utility, understanding the underlying mechanisms of these functions is essential for every developer. In this blog post, we delve deep into the inner workings of these JavaScript powerhouses. We won&#39;t just use them; we&#39;ll deconstruct and reconstruct them, crafting our own custom map, filter, and reduce methods using Array.prototype. By dissecting these functions, you&#39;ll gain invaluable insights into their operations, equipping you to leverage JavaScript&#39;s array manipulation capabilities adeptly.

In modern microservice architecture, powerful messaging systems are the backbone of the system. Kafka is one such messaging system that offers high-throughput stream event processing. Compared to other messaging systems like RabbitMQ, Kafka shines in the amount of messages it can handle, which is millions of messages per second. How does it achieve this? Well, it uses two superpowers: