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"Python is bloat" wait until you look at NodeJS "node_modules" folder
this post was submitted on 18 Nov 2024
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"bloat" is just short for "your computer sucks".
Dump your peasant tier shit and go fill up that 42U rack.
Tbh this all seems to be related to following principles like Solid or following software design patterns. There's a few articles about CUPID, SOLID performance hits, etc
- it all suggests that following software design patterns cost about a decade of hardware progress.
Absolutely not lol.
If SOLID is causing you performance problems, it's likely completely solvable.
Most companies throwing out shitty software have engineers who couldn't tell you what SOLID is without looking it up.
Most people who use this line of reasoning don't have an actual understanding of how often patterns are applied or misapplied in the industry and why.
SOLID might be a bottle neck for software that needs to be real-time compliant with stable jitter and ultra-low latency, the vast majority of apps are just spaghetti code.
I'm happy if it's actually running in python and not a javascript app with electron.
Idk, it's rare for an electron app to literally not even run. Meanwhile I'm yet to encounter a python app that doesn't require me to Google what specific environment the developer had and recreate it.
With a properly packaged python app, you shouldn't even notice you're running a python app. But yeah, for some reason there's a lot of them that ... aren't.
I think with pyenv and pipenv/UV you can create pretty reliable packaging. But it's not as common as electron, so it's a pain.
That's fair.
Ah yes, those precious precious CPU cycles. Why spend one hour writing a python program that runs for five minutes, if you could spend three days writing it in C++ but it would finish in five seconds. Way more efficient!
So, I've noticed this tendency for Python devs to compare against C/C++. I'm still trying to figure out why they have this tendency, but yeah, other/better languages are available. 🙃
Welp, microcontrollers say hi
Welp, I'm not saying you should use Python for everything. But for a lot of applications, developer time is the bottleneck, not computing resources.
Because when it is to actually get paid work done, all the bloat adds up and that 3 days upfront could shave weeks/months of your yearly tasks. XKCD has a topic abut how much time you can spend on a problem before effort outweighs productivity gains. If the tasks are daily or hourly you can actually spend a lot of time automating for payback
And note this is one instance of task, imagine a team of people all using your code to do the task, and you get a quicker ROI or you can multiply dev time by people
SDLC can be made to be inefficient to maximize billable hours, but that doesn't mean the software is inherently badly architected. It could just have a lot of unnecessary boilerplate that you could optimize out, but it's soooooo hard to get tech debt prioritized on the road map.
Killing you own velocity can be done intelligently, it's just that most teams aren't killing their own velocity because they're competent, they're doing it because they're incompetent.
And note this is one instance of task, imagine a team of people all using your code to do the task, and you get a quicker ROI or you can multiply dev time by people
In practice, is only quicker ROI if your maintenance plan is nonexistent.
You can write perfectly well structured and maintainable code in Python and still be more productive than in other languages.
That also goes to show why to not waste 3 days to shave 2 seconds off a program that gets run once a week.
exactly! i prefer python or ruby or even java MUCH more than assembly and maybe C
I mean, I'd say it depends on what you do. When I see grad students writing numeric simulations in python I do think that it would be more efficient to learn a language that is better suited for that. And I know I'll be triggering many people now, but there is a reason why C and Fortran are still here.
But if it is for something small, yeah of course, use whatever you like. I do most of my stuff in R and R is a lot of things, but not fast.
But if it is for something small, yeah of course, use whatever you like.
or if you have a deadline and using something else would make you miss that deadline.
Why would an RTX 4090 make Python faster?
I bet an LLM could have written this meme without making that mistake.
Embarrassing.
Don’t worry this post was written by a first year computer science student who just learned about C. No need to look too closely at it.
Rust is better.
The only language worth discussing is brainfuck
Purest of the programming languages
Joke's on you, he was talking about "Phyton". /s
The new favorite language of AAA game studios: ~~Phyton~~ Python
I know it makes me sound like an of man shouting at clouds but the other day I installed Morrowind and was genuinely blown away by how smooth and reliable it ran and all the content in the game fitting in 2gb of space. Skyrim requires I delete my other games to make room and still requires a whole second game worth of mods to match the stability and quantity of morrowind.
Yes, but also community rewrite of the Morrowind engine, to make it even more better: https://openmw.org/
Admittedly, some changes might make it use more resources, for example it's got basically no loading screens, because nearby cells get loaded before you enter them...
Back in the day morrowind was unoptimised too, https://kotaku.com/morrowind-completely-rebooted-your-xbox-during-some-loa-1845158550
That's fair, though honestly the only issue I ever had on the Xbox was having a loading screen every 5 minutes.
High res textures (especially normal maps) and higher quality/coverage audio really made game sizes take off. Unreal's new "Nanite" tech, where models can have literally billions of polygons, actually reduces game size because no normal maps.
Phyton
Love you homie 💋 walks away
It used to be pretty terrible, but the frameworks are getting there, starting with the languages they are based on.
Believe it or not, Java has been optimized a ton and can be written to be very efficient these days. Another great example of a high-level, high-efficiency language is Julia. And then there is Rust of course, which basically only sacrifices memory-efficiency for C-speeds with Python-esque comfort. It's getting better.