Programming

Who cares if the program takes ten seconds to run instead of one when it only needs to run once and coding it in Python takes a few hours instead of a day or two in C?

If you need performance that badly, by all means, use C. If you have ten ideas for simple programs and just want to code them real quick without fighting the compiler and worrying about all the little shit that C demands from you, then there's nothing wrong with using Python.

Everything in life is a tradeoff. Use the right tool for the job.

define slow.

my life has been in C style languages but even i kniw python us a great general purpose language. are you going to use it for high frequency trading? no but most things dont need that speed.

yes its used a lot in ai but also for a ton of linuc scripting. i dont think anyone uses perl anymore.

so in what way was it slow when you used it? what micro seconds were you lookong for?

People who say "Python is slow" are generally wrong, yes, the language is slower then C in basically everything and it also almost always doesn't matter.

The bottleneck in a console app is not your applications ability to process, it's your ability to read and type, you will have the same experience in any language.

The same is true with GUI apps, python GUI apps are generally just bindings to toolkits written in other languages like pyqt is a python wrapper around a C++ toolkit.

In actual gamedev, something like Pygame is using SDL which is a C library.

YouTube is a python web app.

Yes, python is slow, and generally it doesn't matter, if it's slow then it's usually a PEBCAK problem. Python is primarily used as an easy to write language that is gluing together more complicated things written in faster languages.

Like bash, but readable by humans!

When used for much of the fancier stuff, like AI, it's not running in python. Python is just setting up all the other stuff and making the calls to shove the models onto the GPU and configure and blah blah... You're just writing the program that uses the ML libraries that make other types of programming do the real work, like CUDA or the other one I forgot the name of, or even Vulkan, or what have you.

So while Python is slow, things written in it do not have to be slow.

Similar to Godot's language. It's terribly inefficient, but it's meant mostly to respond to human time scale events, not to have complex computation-heavy systems written up in it. And similar to Python with AI tools and whatnot, Godot's graphics side is still running hot and fast in the GPU with dx/vulcan even while the language the UI and game logic is written in is inefficient.

Things I do in Python don't require speed

What's the point of anything? I have all these Electron apps on my devices which require Gigabytes of memory, Discord took a substantial amount of RAM my old laptop had. There's Android apps which are hundreds and hundreds of megabytes and all they do is call some REST APIs. Lemmy's protocol is terribly inefficient. And back in the day in the 90s an entire office suite fit on a bunch of floppy disks. And a 0.025 GHz CPU was all it took to run it... The internet was so much more efficient, you do your online banking, chat, read the news (without a lot of images) with 0.1% of today's internet connections.

I bought my house migrating days long Excel processes into minutes python script. They could be seconds C++ programs? For sure. But they would be unmaintainable and would take way too much time to write.

By the time you finish your C script, compile it and run, Python developer will already have finished. Speed is relative.

Depending on the project, development speed is often critical. Lots of data science stuff is really ad hoc and doesn't get reused much, just some math, biology etc. graduates doing number crunching on specific datasets. Sure the script might take a day to execute, but if it's only actually getting used a single or double digit number of times, it doesn't make sense to break out more low level languages.

With commercial projects, it's often an issue of whether the higher hardware requirements of a project done in a scripting language are offset by the longer development time and higher wages for sufficiently competent programmers to do it in more low-level languages. This does have environment implications, but commercial projects don't typically give a damn about socialized costs (despite the lip service that many had adopted for a while).

AI seems mental, though, unless Python is just some glue for calling functions or libraries that are implemented in lower-level languages, which is definitely also a thing.

Assuming this is a genuine question and not just trolling.
Python's main feature, IMO, is that it's easy to pick up. You don't need to remember to put a semicolon after nearly every line, so you don't need to remember which lines don't need it. Basically you only need to remember to put a colon before an indented block.
Thanks to significant whitespace even bad code will be moderately legible.
Control flow and loops are basically written in plain English: for i in range(17): as opposed to e.g. for (int i=0; i<17; i++) {.
This all reduces the mental load and thus leaves you with more capacity to focus on the task you're trying to solve.
It's a great language to give to your mathematicians, data scientists and other people with rudimentary programming knowledge at best.

As for the performance: interpreted languages are inherently slower than compiled ones. You don't get a speed boost from first asking a separate program to translate the next line of code into a machine readable format before executing it. Just like you don't get a speed boost from executing all your cod in a virtual machine. Looking at you, Java.
But you don't use python for the compute-heavy tasks. You use it for the plumbing in between and outsource the computation to a native library with python bindings, like NumPy, Pandas, PyTorch, etc. Horses for courses.

In my experience, GUI was horrible because of the GIL. Python is nice because you can write and read it quickly, and packages like numpy allow you to use very natural syntax. Most of the numerical packages wrap C/C++/Fortran binaries which are very optimized. You just have to keep in mind not to do that kind of stuff directly in Python, write tight loops, etc.

Because it is easier to read large codebases of Python than large codebases of Bash.

Slow depends on the use case. If your main bottlenecks are in code that people have written highly optimized lower-level libraries for, it could be slower to roll your own implementation or use a less mature library in a different language. And in some cases it might not matter if you take 1 ms or 100 ms to do something.

It works the other way too, and you have to weigh the pros and cons of your specific case when you choose a language. What level of abstraction do you want to work at, how stable do you need the toolchain to be, how familiar you are with the language, what's supported in the language, how easy is it to do what you want, what's the norm in the domain you're working in, etc.

The NSA has a Github page and I was really surprised to see they use a heck of a lot of Python. This was before the Trump admin.

It's fast enough. People talking about modern CPUs have missed the point that python has been a staple language for gui and web apps for like 20 years.

Easy to whip something quick up.

pish posh

It's easy to pick up

Python is a good first language to learn programming because the syntax is easy (eg. no semi-colons at the end of each line).

In particular you'll be able to switch to Julia with ease.

Looking at the thumbnail I thought it's python logo and 💩. The meme would still work.