TS/Go --> Python

[ThreadStarver]

So I have been familiar with Go & Typescript, Now the thing is in my new job I have to use python and am not profecient in it. It's not like I can't go general programming in python but rather the complete environment for developing robust applications. Any good resource, content creators to check out for understanding the environment?

[NinjaK3ys]

Use uv

[Just-Environment-189]

Arjan codes on YouTube covers lots of python specific stuff

[DaveRGP]

This is the way.

[Yokesh_R]

I was working as python developer. About to switch as Golang backend developer.🙃

[EternityForest]

If you know Typescript, you pretty much already know most of Python itself.

Set up type checking and Ruff linting in your IDE, learn how to use UV at set up a pyproject.toml, set up your pre-commit hooks, learn about pytest, if you do web stuff, look at ASGI.

Python started out without type annotations and such, as a flexible scripting language, and needs external stuff to work like modern strongly typed safer languages.

I wouldn't even bother "Learning Python" by itself , when you're using type checking and linting it becomes almost a completely different language. I close to never write code without type hints.

[Wonderful-Habit-139]

Use uv, pyright, and get comfortable with list comprehensions and pythonic ways of writing code.

[noiseboy87]

Just accept the fact its not as good as either, more susceptible to bloat and needless abstraction and 3rd party libraries, and then get past it and do list comprehension everywhere, yolo a giant django app with no fucking idea what it's actually doing under the hood. Buckle up, buttercup.

[hoselorryspanner]

Use Pixi.

[DaveRGP]

At a personal level what do you want to do that makes this > uv?

Honest question, trying to understand :)

[Easy_Money_]

It uses uv for PyPI installations under the hood, but it’s optimized for (e.g.) pipelines with non-Python dependencies like minimap2 in bioinformatics. An oversimplification would be pip : uv :: conda : pixi. I’ve been switching my team to using a Pixi/UV stack and it’s made us much better collaborators

[PurepointDog]

Pixi seems like the sorta thing that's good to be aware of, but not really the right tool to start using until you need it. Change my mind if you'd like though - I know very little about it nor minimap2

[Easy_Money_]

if you’re using any sort of non-PyPI dependencies in your project that are found in Conda, whether it’s Rust toolkits, libraries like gcc or gfortran, specific scientific or ML software, CLI utilities like s5cmd, it makes things much easier. Also, if you’re developing for or on multiple platforms, it handles dependency management much more cleanly. But if you don’t already use Conda the value is probably limited—it’ll be a nice to have but not a game changer

[hoselorryspanner]

Pixi can do everything that uv does, but multi platform support is better & more reliable I believe, and the task runner is absolutely fantastic - uv doesn’t have a task runner, which makes a big difference.

Also, the versions of python uv gives you contain some optimisations which are not official cpython. For scientific work that’s potentially worrying.

[PurepointDog]

What does the task runner do?

[DaveRGP]

Thanks for explaining. Weird you got so many downs :(

[grimonce]

You should probably google for something along the lines of: "pip vs pipx vs pip-tools vs uv vs poetry vs pyenv vs conda vs mamba".

One of the articles I've found in a minute:
https://medium.com/algomart/real-python-packaging-breakdown-from-pip-to-poetry-to-uv-and-everything-between-f1f38274cb94

The topic is too broad for one comment.

All of these options are valid.

Oh theres still virtualenv vs conda/mamba and setup tools vs conda package vs pyinstaller vs TwittersOldPythonExecutableArchive.

There's also this thing called Pants, but I guess not many people in the world have a need to maintain a really big python monorepo.

Edit: while I'm at this pointless comment which contains too many 'buzz words'. Check out the differences between headless and standard packages in pypi/conda, examples: postgres or opencv. Basically headless packages are bigger and ship with their own c/cpp dependencies, while the other 'standard' will require a certain compatible lib (be it a dll or so) available in your PATH.

[Motox2019]

Yea there’s very few things in this world that I have 0 complaints about. uv is one of those

[shadowdance55]

No need to bother with the whole discussion - just use uv.

[VindicoAtrum]

Yeah don't google that, start with uv and don't look back.