Getting Started with Modular's Mojo Programming Language

Codecademy Team
Master the essentials of Mojo programming for AI development

Welcome to the world of Mojo! In this article, we will introduce you to the basics of Mojo programming language and get you ready to start developing with Mojo.

What is Mojo?

Mojo is a new programming language that combines Python’s usability with C’s performance. It aims to bridge the gap between research and production by incorporating the best features of Python syntax, systems programming, and metaprogramming.

Modular, the company behind Mojo, has granted early access to an online playground: a Jupyter Notebook environment where users can explore Mojo’s functionalities. Mojo is a “superset” of Python, meaning Python programs are valid in Mojo. However, not all Python behaviors are implemented yet.

Mojo provides a unified programming model suitable for programmers of all experience levels. It scales across various use cases, from accelerators to application programming and scripting. Additionally, Mojo supports 26 languages and can be accessed on the web.

Why use Mojo?

Mojo is an excellent choice for developers interested in developing AI-related applications. It provides a high-performance environment for AI model development while retaining the simplicity of Python. With Mojo, developers can create high-performance libraries that would typically require C, C++, Rust, CUDA, and other accelerator systems. Here are the key features that set Mojo apart:

  • Language Syntax: Mojo utilizes all of Python’s syntax and semantics, supporting control-flow structures like if-conditions and for-loops. Functions can be declared using either fn or def, with fn ensuring strong typing.

  • Static vs. Dynamic Typing: Mojo is designed to be a superset of Python, preserving its dynamic features while introducing new primitives for systems programming. This means that type-checking occurs at runtime but also allows for static typing when necessary.

  • Error Handling: In Mojo, exceptions are referred to as Errors. Compared to conventional languages such as C++, Mojo’s error handling is more efficient and predictable, leading to better debugging.

Mojo’s Unique Selling Points (USPs):

  • Enhanced Speed (Performance): Mojo is 35,000 times faster than Python. It is designed to provide C-level performance, which is a significant advantage for performance-critical applications.

  • Compatibility with AI Hardware: Mojo utilizes multilevel intermediate representation (MLIR) to support several types of hardware, including GPUs running CUDA and similar hardware, without adding complexity.

  • Integration with the Python Ecosystem: If you are already familiar with Python, transitioning to Mojo is easy as it is a superset of Python. This means you can leverage your existing Python knowledge and codebase. As a Python superset, it provides seamless access to Python libraries like NumPy.

  • AI and ML (Machine Learning) Support: Mojo is specifically built with AI in mind, making it an excellent choice for developing AI-powered applications.

However, it is important to note that the right programming language depends on specific needs and circumstances. While Mojo has many promising features, it is still in its early stages of development, so there might be some growing pains as the language evolves. It is always a good idea to thoroughly evaluate any innovative technology before deciding to adopt it.

More on Mojo’s Capabilities:

Mojo’s Object-Oriented Programming (OOP): Mojo offers enhanced support for OOP with a simpler syntax. One innovative feature of Mojo is its morphing syntax, which adapts to our preferred programming style, be it functional, object-oriented, or procedural. For example, if we prefer an object-oriented approach, we can use the following syntax:

# Create an instance of the Math class
math = Math()
# Call the square method and print the result
print(math.square(5)) # Outputs: 25

This code creates a new instance of the Math class, calls the square method on that instance with the argument 5, and then prints the result (25) to the console.

Asynchronous programming and concurrency in Mojo: In Mojo, we can write concurrent code using lightweight, asynchronous tasks called fibers. Fibers are a programming construct that enables concurrency, often considered lightweight threads. They are called “lightweight” because they have a smaller overhead than traditional threads due to sharing the same execution context. Fibers are more efficient than threads and make concurrent code easier to understand and maintain. With Mojo’s built-in concurrency model, you can write efficient and performant code without dealing with the complexities of threads, locks, and synchronization.

Libraries and Frameworks: Mojo is a collection of runtime libraries that provide a platform-agnostic abstraction of common IPC (Inter-Process Communication) primitives, a message IDL (Interface Definition Language) format, and a bindings library with code generation for multiple languages. It also allows leveraging the entire Python library ecosystem, including popular tools like NumPy.

Definitions:

IPC (InterProcess Communication) refers to a set of programming interfaces that allow processes to communicate with each other. This communication can occur between processes running on the same computer or on different computers.

IDL (Interface Definition Language) is a specification language used to define the interfaces that programs use to communicate with each other. An IDL is platform-independent, meaning it can be used to define interfaces and data types regardless of the programming language the applications are written in.

The Mojo Software Development Kit (SDK):

The Mojo SDK is a comprehensive set of tools for developing applications using the Mojo programming language. Here’s why it’s essential:

  • Complete Development Tools: The Mojo SDK includes all necessary resources for local Mojo development, such as the Mojo standard library and the Mojo command-line interface (CLI).

  • Ease of Use: The SDK provides developer and Integrated Development Environment (IDE) tools that make building and iterating on Mojo applications easy.

  • Cross-Platform Support: Currently available for Ubuntu Linux and macOS systems running on Apple silicon. Windows support is coming soon.

  • Integration with Visual Studio Code: Mojo extension available for Visual Studio Code, offering features like code completion and hover help for Mojo APIs.

  • Regular Updates: Mojo is an ongoing project, with regular updates for the language and SDK tools to provide the latest features and improvements.

Installing the Mojo SDK

To get started with the Mojo SDK, you will need to install it on your machine. You can download the latest version from the official Mojo website. As of this writing, Mojo is not available for Windows, but can be installed:

  • In a Docker container
  • On a Linux distribution
  • Or by using the Windows Subsystem for Linux (WSL) and Visual Studio Code

Writing Your First Program

After you have installed Mojo, you can write your first program! Open your favorite text editor and create a new file called “hello_world.mojo”. In this file, type the following code:

print("Hello, World!")

Save the file and run it using the following command:

mojo hello_world.mojo

You should see the following output:

Hello, World!

Congratulations! You’ve just written your first Mojo program.

Conclusion

We introduced you to the basics of Mojo programming language. We covered what Mojo is, why you should use it, how to install it, and how to write your first program. We hope this tutorial has been helpful in getting you started with Mojo. Happy coding!

To see what else you can do with ChatGPT (or generative AI in general), check out some of the topics covered in the articles located here: AI Articles.