Here’s my 2¢. Debian is a reasonable OS to develop on, since it provides a super stable and reasonably secure base platform. I’ve used it quite extensively for the same purpose without any issues whatsoever.

However, it won’t satisfy the needs of the modern style of development. For that, you need a reproducible development environment so that every developer gets the same results. (That means avoiding the ‘it works for me’ type of bugs). That means you need the same version of runtimes (python), same version of libraries/dependencies and same developer tools on every development system, irrespective of the distro it’s running on.

The problem with Debian is that it often ships older versions of software to keep it stable. It will likely not match the version of python and tools you need. For that matter, no distributions including the frequently updated Arch Linux are likely to meet those requirements. (There are exceptions - NixOS and Guix.) So the widely adopted solution is to create a dev environment independent of your core system, from your regular non-root account. That means separately installing a python runtime that’s different from your distro repo, etc. They don’t touch your core system and keep it clean and pristine.

The way we achieve this is by using 4 tools:

1. Runtime version manager: Manages the version of runtimes.

• Eg: python: pyenv, node: nvm, rust toolchains: rustup

2. Environment manager: Creates and maintains isolated environments where the correct runtimes, project dependencies and tools are available.

• Eg: python: venv, node: node project, rust: rust project

3. Dependency manager: Resolves and installs the correct version of all project dependencies into the environment.

• Eg: python: pip, node: npm, pnpm, rust: cargo add

4. Tool manager: Installs additional development tools for the project, like formatter, linter, etc.

• Eg: python: pip, pipx, node: npx, rust: cargo install

Often, many of these are combined and you may get less than 4 different tools. The current situation is extremely complicated and there are many different tool combinations you can use. So let’s address your specific requirements.

If your project uses only Python

In this case, the choice is pretty straightforward. Use uv.

The package management situation in the Python ecosystem was an absolute mess until UV appeared on the scene. UV combines all the 4 functions I mentioned above. It replaces venv, pyenv, pip and pipx in a single fast binary. You’ll be surprised by its speed if you’re used to the speed of pip. It’s easy to use and very well integrated. It also integrates additional functionalities like:

• Formatter (replaces black)
• Project setup (helps with poetry, flit, hatch, etc)
• Project publishing (replaces twine)

If you will use more than Python

If you will use tools or languages other than Python in a single project or in other future projects, you might want to use a ‘language-agnostic runtime and tool manager’. They can manage runtimes and tools of multiple languages. Dependencies have to be managed using language package managers (like UV, pip, cargo, npm, etc).

The most well known tool manager is asdf. Others include aqua, vfox, etc. But the upcoming star is mise. I use mise for multiple projects including for Python projects. Mise uses UV behind the scenes for Python. So, mise projects play well with UV projects and with others who use UV.

The only disadvantage with multitool managers like asdf and mise is that they tend to be more complex compared to single language tools like UV. They obviously handle more and provide more features. However, investing time in tools like mise pays in the long run when you’re handling multiple languages.

Servers like databases

The tools I mentioned above don’t handle daemons like postgresql, redis, etc. This is why your colleagues recommend VMs. I will talk about VMs in a while. But I want to show you some simpler solutions here.

Another commenter has already mentioned the use of docker-compose files to set up such servers. It’s the easiest solution possible.

Another more refined solution specifically for development containers is testcontainers. It’s essentially the same as the docker compose solution, but with more dials and switches to help with automated tests like unit tests during CI. You’ll have to learn a bit more than docker compose, to use it. However, those test servers are also readily available online and require little configuration.

Do you need virtualbox?

The methods explained above don’t ruin your base Debian install. So a dedicated VM is not really required. However, I’m leaving this information here for completeness.

Use of VMs was widespread in the past. But they didn’t run virtualbox, VMware or Qemu directly. Instead, a CLI frontend tool was used to set up those VMs for development. The most common tool was Hashicorp’s Vagrant. Another tool available today is Lima. These tools mount your project directory into the VM, set up its network, install required tools, start required services (like DBs), attach a shell for you to work on, etc. These VMs are complete development environments and you don’t need to do anything on the host system other than starting them up.

Since the advent of containers, the same idea has been implemented using containers instead of VMs. These are obviously less resource intensive than VMs. Most of them follow the devcontainers standard. So a devcontainer configuration works on multiple platforms, including GitHub’s famous codespaces. Local tools for it include devpod, ona, devbox and devenv.

Conclusion

There are a lot more solutions. But these are the ones you’re most likely to settle on. So I leave it at that. Please let me know if you have any questions about this reply. Hope you find your favorite setup soon.