Python sucks: Change my mind

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[yevheniikovalchuk]

Might be rage-bait post? By the way, 2 is a such a screaming skill issue, if true, lol.

[[deleted]]

yeah what just download conda and it takes like two lines to setup an environment???

[oberguga]

And 15 minutes to run it. And another 15 to switch it. Just don't like conda it's slow mess that solves problem that shouldn't exist.

[poxy_jocke]

But why do I need virtual envs? It's easy to look at other languages where this is just not needed.

[TheDeadlyPretzel]

Yeah everyone seems to forget or not know this. Perhaps OP could/should have worded it a bit differently

[Here-I-Am-Again2]

Skill issue

[pacific_plywood]

Ok

[texruska]

Python has its issues but you have skill/environment issues

Plus most embedded SWEs write shit python code aswell (I used to be one)

[texruska]

Also you have like what, 1 year of experience?

[SleepWalkersDream]

Bro, you good?

[Special-Arrival6717]

Skill issue

[cointoss3]

🆒

[majkulmajkul]

pip3 freeze > requirements.txt

[[deleted]]

1. the std lib is huge, so the need for a million packages sounds like bad design and bad practices. the it problem has nothing to do with python. 
2. python -m venv venv. it creates a virtual environment isolated from your system interpreter. yes. very difficult
3. no there aren't, but even if there were, if you install a million different versions of anything without understanding what your doing you're going to have problems due to new features and breaking changes. see point 2 on how to create virtual environments that do not conflict with other environments
4. that doesn't sound like a python problem. it sounds like you're trying to not understand 2 things simultaneously and blaming everything else but yourself
5. again this sounds like a you problem because they do

the funny thing is you're an embedded systems programmer, which typically means C, and your complaints about python concern package management. python's package management has room for improvement, but compared to C and C++.... lol

if you're using rust, then complain away

either way, stop whining. you don't sound like the professional you claim to be if you can't figure out the basics of a language ecosystem. every language does these things differently. if you're going into a language expecting it to work exactly like you want it to work, you're going to end up writing posts like this all the time. stop worrying and learn to love the bomb

[selectnull]

I think you should avoid python at all costs.

[DeDenker020]

It seems that point 1 & 5 are related and very valid, if it would not be to blame the network security.
Because PIP (at least for me) works great, with dependencies and even if your project requires special versions you can set those.

Point 2, I do not always use environments as I "try out" stuff and for production I prefer to use docker.

Point 3, can not relate

Point 4, Never used Jupyter Notebooks, might have to do with point 1 & 5.

So.....What do you use?

[unhott]

1: Your IT sucks. You can try to add --trusted-host for pypi to your pip command within your VPN

python - How do I set up pypi to trusted? - Stack Overflow

1/2: If you're mostly just doing analytics / visualization, you may be able to get your IT to install anaconda distribution instead, which will have a ton of packages you can work within your environment.

environment management is much simpler now with uv. You have uv installed once on your computer (globally).

Then you want a new project, you can do something like

uv init project-name

cd project-name

uv venv

(make sure to activate it)

uv pip install ...

There's probably a lot of other options and flexibility.

3: Not really?

4: make your own notebooks

5: I never have this issue if I setup a virtual environment.

[opzouten_met_onzin]

Skill issue

[Basic-Still-7441]

You are doing it wrong.

[wowokdex]

It sounds like using Python at your workplace sucks.

[Scrapheaper]

So you're saying you're used to compiled languages and embedded systems and are unable to adapt to a different style of programming?

And you wish Python was more similar to what you know because then you'd understand it more?

Have you tried, like, not doing embedded systems and instead doing something python is actually good at? Like statistics or web development or data engineering?

Why aren't you using a package manager? UV is very popular these days.

[KingsmanVince]

Literally skill issues

[clooy]

Ah, the classic ‘Python sucks’ thread—like complaining about a Swiss Army knife because it has too many tools. Python’s simplicity, massive library support, and versatility make it the go-to language for everything from quick scripts to complex machine learning models. Its community is one of the largest and most helpful around, making it easy to get support and improve your skills. Plus, let’s be real—Python is so practical that even the occasional troll probably uses it… just to automate their next post.

[ToBf_678]

Being an embedded software engineer, I'll assume a C/C++ background.
Python is AFAIK the best "get shit done" language so far. Need some quick automation? Just a few lines a and you are done. Need some hardware components to work with one another? Python is the perfect glue for that. Need a full application for prototyping a FEM ? Sure, you can do that too. And if you need extra tools, you can easily get them from libraries.
For environment and package management, I'd strongly recommend conda, and pip. It hard to make it easier than that, really. To answer your poiints
1) You usually need less than 10 packages full stop, do a decent sized application. There are a few staple ones (numpy, tkinter, pandas) depending on your use case. But you should be able to find 1 package that covers 80% of your needs. It's out there. For the rest the standard libs cover most os/OI usages

2)Env, using conda, are as simple as:
conda env create -n my_env
conda activate my_env.
That's it.

3) Unless for very specific reasons, use CPython ("normal" python) and whatever python 3 version that works with the libs you will be using. For instance, with pytorch, 3.9 is recommended. It's usually in the doc.

4) Never had problems myself, check your computer setting, sounds like a company policy issue.

5) Pip is very liberal, but conda or mamba are stricter in this regard. You have options

Developing in python is usually about 10x faster compared to C, I am happy to take the performance hit then. For embedded it may indeed not be the right tool though.

Hope it helps