If you’d like to redefine a variable across notebook cells, you must introduce the variable with var ( let variables are immutable). Redefining implicit variables is not supported (variables without a let or var in front). However, we’ve included a variety of popular Python packages, such as numpy, pandas, and matplotlib (see how to import Python modules). The Mojo environment does not have network access, so you cannot install other tools or Python packages. Rename the files if you want to save your changes. Variables, functions, and imports defined in a Python cell are available for access in subsequent Mojo cells.ĭid we mention that the included notebooks will lose your changes? You can use %%python at the top of a notebook cell and write normal Python code. So if you rename the files, your changes will be safe. These files will reset upon any server refresh or update, sorry. If you want to keep any edits to the included notebooks, rename the notebook files. Please report issues and feedback on GitHub. However, as you will see in the included Matmul.ipynb notebook, Mojo’s relative performance over Python is significant. The number of vCPU cores available in your cloud instance may vary, so baseline performance is not representative of the language. We’ve included a handful of notebooks to show you Mojo basics and demonstrate its capabilities. The Mojo Playground is a JupyterHub environment in which you get a private volume associated with your account, so you can create your own notebooks and they’ll be saved across sessions. To get access, just log in to the Mojo Playground here. This is a hosted version of JupyterLab that’s running our latest Mojo kernel. Instead of downloading the Mojo SDK, you can also experiment with Mojo in our hosted Jupyter notebook environment called Mojo Playground. Use the following link to log into the Modular developer console, where you can get the Modular CLI and then install Mojo:īrew update brew upgrade modular Develop in the Mojo Playground The Mojo SDK is available through the Modular CLI tool, which works like a package manager to install and update Mojo. Support for Windows will be added in a future release. x86-64 CPU (with SSE4.2 or newer) and a minimum of 8 GiB memory.To use the Mojo SDK, you need a system that meets these specifications: We’ve also published a Mojo extension for Visual Studio Code to provide a first-class developer experience with features like code completion, quick fixes, and hover help for Mojo APIs. The Mojo CLI can start a REPL programming environment, compile and run Mojo source files, format source files, and more. The Mojo SDK includes everything you need for local Mojo development, including the Mojo standard library and the Mojo command-line interface (CLI). Alternatively, you can also experiment with Mojo using our web-based Mojo Playground. You can also develop from Windows or Intel macOS using a container or remote Linux system. The Mojo SDK is currently available for Ubuntu Linux systems and macOS systems running on Apple silicon. Mojo is now available for local development!
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