Prepros vs gulp: What are the differences?

## Introduction
This Markdown code provides a comparison between Prepros and gulp in terms of key differences for website development purposes.

## 1. **User Interface**: Prepros offers a user-friendly graphical interface, making it easier for beginners to use without prior coding knowledge. On the other hand, gulp relies on configuration through code, which might be more suited for advanced users who prefer a more hands-on approach.

## 2. **Automation**: Prepros automates various tasks like compiling Sass, Less, CoffeeScript, minifying files, and browser refreshing with just a few clicks. Gulp, however, requires defining tasks in JavaScript, which provides more flexibility and control over the automation process.

## 3. **Plugins and Ecosystem**: Prepros comes with built-in support for various preprocessors and plugins, reducing the need for additional setup. Gulp, being a task runner, has a vast ecosystem of plugins available, giving developers the ability to customize their workflows extensively.

## 4. **Performance**: Prepros is known for its simplicity and ease of use, which can lead to faster setup and quicker compilation times for smaller projects. Gulp's performance shines when dealing with larger projects due to its code-over-configuration approach, optimizing the build process for efficiency.

## 5. **Community Support**: Prepros has a smaller but dedicated community, offering reliable support and assistance for its users. Gulp, being an open-source project, has a larger community with active contributors, providing a wealth of resources, tutorials, and updates.

## 6. **Learning Curve**: Prepros has a lower learning curve, making it ideal for beginners or those looking for a quick and simple build tool. Gulp, while more complex initially, offers a more in-depth understanding of build processes and task automation, suitable for developers looking to enhance their skills and workflows.

In Summary, the key differences between Prepros and gulp lie in their user interface, automation capabilities, plugins and ecosystem, performance, community support, and learning curve.