MLOps Zoomcamp 1.2 - Configuring Environment with GitHub Codespaces

Summary

This video tutorial demonstrates how to quickly set up a course environment using GitHub Codespaces. It covers creating a repository, launching a Codespace, installing necessary tools like Anaconda, and running Jupyter notebooks seamlessly in the cloud. With pre-installed tools like Docker and Python, users can avoid complex local setups. The video also explains how to commit and push homework to GitHub and manage Codespace usage. Ideal for students who want an easy and efficient way to work on assignments without worrying about system configurations.

Takeaways

• 😀 GitHub Codespaces is a simple and efficient alternative to setting up local environments for coding courses.
• 😀 You need a GitHub account to begin and create a new public repository for your project, such as 'melops Zoom Camp'.
• 😀 It's important to make the repository public for easy access and homework submission in the course.
• 😀 GitHub Codespaces provides a cloud-based environment with preconfigured Docker and Docker Compose, saving setup time.
• 😀 To use GitHub Codespaces locally, install Visual Studio Code and the GitHub Codespaces extension for seamless integration.
• 😀 With Codespaces, you can work in a browser-based Visual Studio Code environment, simulating local setup without latency.
• 😀 Ports can be forwarded from Codespaces to your local machine for running services like Jupyter notebooks or MLflow.
• 😀 Installing Python, Anaconda, or other necessary packages is simplified within the GitHub Codespaces environment.
• 😀 Once Anaconda is installed, you can use Python versions like 3.9, even if the default system version is different.
• 😀 After completing homework tasks (e.g., running Jupyter notebooks), you can easily push updates to GitHub without complex configurations.
• 😀 You can stop your Codespace at any time, and it will automatically save any changes, allowing for future work continuation.

Q & A

What is the purpose of this video?

The purpose of this video is to show how to configure the environment for a course using GitHub Codespaces as an alternative to other environment setup methods. It provides a simpler and quicker solution.

Why is GitHub Codespaces considered easier than the alternative method mentioned?

GitHub Codespaces is considered easier because it has many pre-installed tools like Docker and Docker Compose, eliminating the need for manual installation and configuration, which would otherwise require more setup steps.

Do I need a GitHub account to use GitHub Codespaces?

Yes, you need a GitHub account to create a repository and use GitHub Codespaces for setting up your environment.

What are the steps for creating a repository on GitHub for this course?

You need to go to your GitHub account, click on 'New' repository, name the repository, add a README file, and choose a 'Python' .gitignore template. Make sure to set the repository to 'public'.

What is the role of Docker in the GitHub Codespaces environment?

Docker is pre-installed in GitHub Codespaces, and it allows you to run Docker containers directly from the environment. This eliminates the need for additional setup like installing Docker manually.

Can I run Jupyter Notebooks in GitHub Codespaces?

Yes, you can run Jupyter Notebooks in GitHub Codespaces. The video demonstrates how to start a Jupyter Notebook server, forward the ports, and open the notebook in a browser.

Why do I need to open GitHub Codespaces in Visual Studio Code Desktop?

You need to open GitHub Codespaces in Visual Studio Code Desktop because certain tasks, such as running Jupyter Notebooks or MLflow, require port forwarding which cannot be done effectively in the browser version of Codespaces.

What steps are required to install Anaconda in GitHub Codespaces?

You need to download the Anaconda installer using a command like 'wget', run the installation script, accept the license agreement, and choose the default installation location. After installation, you need to initialize Anaconda and open a new terminal window.

How do you configure Python version in GitHub Codespaces?

After installing Anaconda, you can confirm the Python version by running the 'python -V' command. The video shows how to use Python 3.9 from Anaconda instead of the system's Python version (3.10).

How can you push your homework solution to GitHub from GitHub Codespaces?

You can push your homework solution by using Git commands like 'git add', 'git commit', and 'git push' from the terminal in GitHub Codespaces. After that, the solution will be visible in your repository on GitHub.

What should you do if you want to stop using GitHub Codespaces?

You can stop GitHub Codespaces by clicking the 'Stop' button in the GitHub interface. Codespaces automatically saves your progress, and you can resume work later. To completely remove the environment, you can delete the Codespace.

What are the pricing details for using GitHub Codespaces?

GitHub Codespaces offers a free tier up to 120 hours of use per month. After that, there may be charges for additional usage. However, for most users, the free tier should be sufficient.