The MEAN stack offers an engaging environment for developing cloud-native, fullstack JavaScript applications. Comprising an array of open-source components, MEAN provides a robust framework for constructing dynamic web applications from the user interface right down to the database.

Understanding the MEAN Stack

The MEAN stack consists of four primary components that work uniformly to facilitate web application development:

  • MongoDB: A flexible document database that stores information as JSON (JavaScript Object Notation) documents.
  • Express: A back-end web application framework designed to run on Node.js.
  • Angular: A front-end application framework responsible for running JavaScript code in users’ browsers, ensuring a dynamic UI.
  • Node.js: A JavaScript runtime environment that allows your application’s back-end to be implemented in JavaScript.

Pre-requisites for Getting Started

To embark on your MEAN stack adventure, make sure you have the following installed:

Installation Steps

Standard Installation

Follow these commands to clone the repository and set up your environment:

git clone https://github.com/linnovate/mean
cd mean
cp .env.example .env
yarn
yarn start (for development)

Docker-Based Installation

If you prefer using Docker, ensure your version is at least 19.03.0. Then, follow these commands:

git clone https://github.com/linnovate/mean
cd mean
cp .env.example .env
docker-compose up -d

MEAN Stack Approach: A Handy Analogy

Think of the MEAN stack as a well-organized restaurant where each component plays an essential role:

  • MongoDB is the pantry where all the ingredients (data) are stored. Just like in a restaurant, you want your ingredients to be fresh and accessible.
  • Express is akin to the kitchen staff who combine these ingredients to prepare delicious dishes (requests and responses). They handle the orders in the back, ensuring everything runs smoothly.
  • Angular acts like the servers who bring the delicious dishes from the kitchen to the customers (browser), making the experience interactive and lively.
  • Node.js serves as the restaurant itself, providing the space (runtime environment) for this entire operation to function. If the restaurant is not properly set up, the dining experience fails.

Troubleshooting Tips

If you encounter issues during setup or development, consider the following troubleshooting strategies:

  • Ensure all your pre-requisites are correctly installed and their versions are compatible.
  • Check for errors in your terminal and read the messages thoroughly—they can guide you toward a solution.
  • For issues related to MongoDB, ensure that the service is running and your configurations are correct.
  • If you are using Docker, ensure that your containers are up and running smoothly.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Credits

The MEAN name was coined by Valeri Karpov, while the initial concept and development were spearheaded by Amos Haviv and sponsored by Linnovate, inspired by the great work of Madhusudhan Srinivasa.

About the Author

Hemen Ashodia

Hemen Ashodia

Hemen has over 14+ years in data science, contributing to hundreds of ML projects. Hemen is founder of haveto.com and fxis.ai, which has been doing data science since 2015. He has worked with notable companies like Bitcoin.com, Tala, Johnson & Johnson, and AB InBev. He possesses hard-to-find expertise in artificial neural networks, deep learning, reinforcement learning, and generative adversarial networks. Proven track record of leading projects and teams for Fortune 500 companies and startups, delivering innovative and scalable solutions. Hemen has also worked for cruxbot that was later acquired by Intel, mainly for their machine learning development.

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