devpod VS Visual Studio Code

We recommend using the Dev Container configuration with Visual Studio Code (VS Code) or DevPod to ensure a consistent development experience across different computers and environments. It may sound complicated, but it is as easy as a breeze!

When you push your code to Github, you can develop the app using codespace and it will automatically set up an online development environment for you. Other tools will make your life easier when developing using a dev container e.g. DevPod.

DevPod is that new kid in town that works on the same standard of devcontainers.json that Codespaces uses but is on the infrastructure of your choice and is open source. The project was just launched this May and has gathered more than 5.3K stars in this period. The advantage is the lower costs (around 5-10 times cheaper than cloud VMs) with auto-shutdown.

For students, unless there are allocated server resources with network access, it SHOULD/MUST scale down to one local offline ARM64 node (because school districts haven't afforded containers on a managed k8s cloud for students at scale fwiu, though universities do with e.g. JupyterHub and BinderHub [4] and Colab).

For Chromebook sysadmins, Instructors, and Students learning about how {Linux*, ChromiumOS, Android, Git, Bash, ZSH, Python, and e.g. PyData Tools supported by NumFOCUS} are developed, for example;

When you git commit to a git branch, and then `git push` that branch to GitHub, and create a Pull Request, GitHub Actions runs the (container,command) tasks defined in the YAML files in the .github/workflows/ directory of the repo; so `git push` to a PR branch runs the CI job and the results are written back as cards in the Pull Request thread on the GitHub Project; saving to the server runs the (container,command) Actions with that revision of the git repo.

Somewhat-equivalent GitOps CI Continuous Integration workflows (without Bazel or Blaze or gtest or gn, or GitHub Enterprise or GitHub Free due to the kids' intererests) that might be supported at least in analogue by Education and Chromebooks: k8s with podman-desktop in a VM, Gitea Actions (nektos/act; like Github Actions), devpod

devpod: https://github.com/loft-sh/devpod :

> Codespaces but open-source, client-only and unopinionated: Works with any IDE and lets you use any cloud, kubernetes or just localhost docker. (with devcontainer.json, like Github Codespaces)

devcontainer.json is supported by a number of tools; e.g. VScode, IntelliJ,: https://containers.dev/supporting

repo2docker has buildpacks (like Heroku and Google AppEngine).

repo2docker buildpacks should probably work with devcontainer.json too?

repo2docker docs > Usage > "REES: Reproducible Execution Environment" describes what all repo2docker will build a container from: https://repo2docker.readthedocs.io/en/latest/usage.html

jupyterhub/repo2docker builds a Dockerfile (Containerfile) from git repo (or a Figshare/Zenodo DOI) that minimally has at least an /environment.yml and /example.py (and probably also at least a /README.md to start with), and installs a current, updated version of jupyter notebook along with whatever's in e.g. /environment.yml per the REES spec. [1][2][3]

[1] repo2docker/buildpacks/base.py: https://github.com/jupyterhub/repo2docker/blob/main/repo2doc...

[2] "Make base_image configurable" https://github.com/jupyterhub/repo2docker/commit/20b08152578...

[3] repo2docker/buildpacks/conda/environment.py-3.11.yml:

Also see https://devpod.sh/ which has had quite a lot of exposure on HN recently.

For these reasons, I believe most developer environments should prioritize developer experience over fidelity. Tools like Containerized development environments and cloud emulators can strike the right balance and there’s no surprise that we see increased activity around devcontainers, and similar solutions.

Have you considered devcontainers?

Its use results in carrying entire development environments with you, while not cluttering your host OS.

Using DevPod (https://devpod.sh/) ypu are not locked into Visual Studio or Visual Studio Code, but you can use whatever tool you want.

IMO this kind of setup will provide a much better DX than running a bunch of VMs eating away the resources of your laptop.

For beginners, the best code editor is Vscode.

An IDE or text editor; we'll use Visual Studio 2022 for this tutorial, but a lightweight IDE such as Visual Studio Code will work just as well

Choosing IDE: Selecting the right Integrated Development Environment (IDE) can make your coding experience smoother. Consider popular options like as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and configure it to work with Python.

It all starts with the editor. Visual Studio Code (VS Code) is my go-to editor. I was using the Insider’s Edition for the longest time, but some extensions would try to log in and redirect to VS Code regular edition, so I decided to go back to it. That said, VS Code Insider's is very stable.

Meanwhile, a developer workflow that does not require access to AWS Management Console may provide a better experience. As a developer, I appreciate having an integrated development environment (IDE) such as Visual Studio Code where I can code, deploy, and test in one place.

Good to know: If you're a Visual Studio Code user, you can enhance your coding experience by installing the ESLint and Prettier extensions. These extensions provide real-time error and warning highlighting, as well as automatic formatting and code fixing on save.

Download any code editor e.g. VS code. Visual Studio code which is a code editor with support for development operations like debugging, task running, and version control. Go to https://code.visualstudio.com

A code editor (VS Code is my go-to IDE), but feel free to use any code editor you're comfortable with.

First, grab your favorite command-line tool, Terminal or Warp, and a code editor, preferably VS Code and let’s begin.

C# is very good as a language, have developed in it for 5+ years. The problem is the gap between what MSFT promises to management and actually delivers to developers. You really really need to fully read the fine print, think of the omissions in documentation and implement a proof-of-concept that almost implements the full solution to find out the hidden gotchas.

For example, even probably their best product VS Code only got reasonable multiple screens support last year: https://github.com/microsoft/vscode/issues/10121#issuecommen...

And then, on the other end of the spectrum, you have Teams.