Python developers at big companies what is your setup?

I have been forced into VS Code due to a heavy handed push to use more AI stuff and Copilot in VS Code being the blessed way to do that.

Whatever is sanctioned by the IT department and has been hammered into the permission system. Red tape all around.

And when a new enterprise tool is purchased it may or may not change.

(I only believed it once it was lived through.)

Black is the main thing you want IMO.

I think language servers and autocomplete are much more useful for .net (I used to do a lot of C# as a freelancer in college) than they are for python. Personally I just open a REPL and tab around in that if I need it but I do that maybe once a month. Most software is well organized enough you can keep the theory in your head enough for the default nvim config to work easily.

Python just isn't that verbose.

I'm sorry, can't suggest much, I just use `Neovim` and `ripgrep` search. No AI, no autocompletion, no fancy plugins. At the moment I'm working for one of the biggest Python codebases: Odoo - a general purpose ERP from Belgium.

What do you mean by “tool”? Do you mean IDE/editor, or something else?

Sorry "working with LLMs" is not enough context to compare .NET and Python environments without resorting to LLMs. People actually use for what?

At EntwicklerHeld we used a setup i was happy with:

- poetry for dependency management

- black for formatting

- flake for linting (you can use ruff now)

- PyCharm as IDE

- pyenv for python version management -> but I switched to devbox a year ago and never go back

- docker as end artifact

- deployed to kubernetes (at the end k3s) with ansible and terraform

UV has become my goto for package/venv management. It can work as a close to dropin replacement for pip.

Ruff is my goto for linting and formatting. replacing black, isort, flake8, etc.

There's lsps for both, so you can use them in vscode or wherever you're doing your editing.

UV for packaging and dependency management, Ruff for linting, Mypy for type checking (will be likely replaced by Ty when ready) and whatever editor people like (PyCharm, VSCode, Helix...)

The "basics":

  Vim + PythonMode
  `python -m venv` for local environment separation
  Git + https://github.com/dandavison/delta for change management

When I need a debugger or a Git GUI, VScode, but Zed is becoming more and more interesting. These support LLM interaction, but things like Claude Code fit better with the above list.

Can you use vscode devcontainers?

Can you use a dev container with a dockerfile and use UV for package management, ruff for formatting and lint, mypy for type hint checking, and pytest.

And put all of that on your CI as well so if they fail you don’t merge failing code.

VS Code and local Python virtual environments.

Packages managed with pip and versions pinned with pipcompile. One ML production environment forces us to use conda we inherit from the pip environment and try to have as much done by pip as possible.

Formatted with black and flake8

Unit tests with unittest

Azure Dev Ops for running tests, security screening, and CI

The happy path for deployment is build docker images in AzureDevOps unfortunately we can’t do that for good reasons

* pyenv for python version management

* poetry for package manager

* vscode + copilot

I can't answer OP as I only write Python for personal use, not for a "big company".

That said, Neovim + basedpyright + pipenv works well for me.

A lot of people here are using uv and pyenv. Can anyone hint at why I might want to switch?

Not a big company, however:

- uv (went from pipenv to poetry to uv), which was the right decision imo.

- ruff (replaced black)

- PyCharm, but some people use vscode or neovim.

- mypy for type checking, which I am not 100% happy with. One experienced developer swears by mypy, thats the reason we haven't explored alternatives.

- 'just' as task runner

Zed is worth a look for your IDe and plays nicely with LLMs

What people use is going to be very environment biased. For example scientific research uses conda a lot, but I've rarely seen it used by code devs. People using only python will often have more system wide setup with tools and linters than those mixing different projects. Also you'll see some deprecated in tool use in projects which are older and not worth changing without a good reason. Etc.

With that out of the way: mise for managing versions of all the runtimes (asdf is fine too), uv for packages (previously poetry which is ok), mypy type checking for things I make. Otherwise I switch between projects a lot so just use whatever the projects use by default.

Deployment tools aren't really language specific (when they are they're rarely good). The editing, it's just Cursor, although I did like the jetbrains IDE previously.

But overall - just give things a go. It's usually quite easy to swap those tools as needed.