Many of these have C-bindings for their libraries, which means that slowness is caused by bad code (such as making a for loop with a C-call for each iteration instead of once for the whole loop).
I am no coder, but it is my experience that bad code can be slow regardless of language used.
Bad code can certainly be part of it. The average skill level of those coding C/C++/Rust tends to be higher. And modern programs typically use hundreds of libraries, so even if your own code is immaculate, not all of your dependencies will be.
But there’s other reasons, too:
Python, Java etc. execute their compiler/interpreter while the program is running.
CLIs are magnitudes slower, because these languages require a runtime to be launched before executing the CLI logic.
GUIs and simulations stutter around, because these languages use garbage collection for memory management.
And then just death by a thousand paper cuts. For example, when iterating over text, you can’t tell it to just give you a view/pointer into the existing memory of the text. Instead, it copies each snippet of text you want to process into new memory.
And when working with multiple threads in Java, it is considered best practice to always clone memory of basically anything you touch. Like, that’s good code and its performance will be mediocre. Also, you better don’t think about using multiple threads in Python+JS. For those two, even parallelism was an afterthought.
Well, and then all of the above feeds back into all the libraries not being performant. There’s no chance to use the languages for performance-critical stuff, so no one bothers optimizing the libraries.
For example, when iterating over text, you can’t tell it to just give you a view/pointer into the existing memory of the text. Instead, it copies each snippet of text you want to process into new memory.
As someone used to embedded programming, this sounds horrific.
Yep. I used to code a lot in JVM languages, then started learning Rust. My initial reaction was “Why the hell does Rust have two string types?”.
Then I learned that it’s for representing actual memory vs. view and what that meant. Since then I’m thinking “Why the hell do JVM languages not have two string types?”.
I’m not a java programmer, but I think the equivalent to str would be char[]. However the ergonomics of rust for str isn’t there for char[], so java devs probably use String everywhere.
Idk numpy go brrrrrrrrrr. I think it’s more just the right tool for the right job. Most languages have areas they excel at, and areas where they’re weaker, siloing yourself into one and thinking it’s faster for every implementation seems short sighted.
At it’s heart, numpy is C tho. That’s exactly what I’m talking about. Python is amazing glue code. It makes this fast code more useful by wrapping it in simple® scripts and classes.
Energy use? That’s a pointless metric. If that is the goal then whole idea of desktop should be scraped. Waste of memory and hard drive space. Just imagine the amount of energy wasted on booting GUI.
If you want to talk about climate change then electronics is the wrong place to point the finger at. For start look at cement manufacturing. It requires huge amounts of energy to produce even though we have eco-friendly variants ready to go. And cement production amounts to 8% of all greenhouse gasses released annually.
Hell, just ban private jets and you’ve offset all of the bad things datacenters ever made. Elon had 10 minute flight to avoid traffic which consumed around 300l of fuel. Royal family makes so many flights a year that you could go into the wild and eat bark until the rest of your life and you wouldn’t be able to offset their footprint in thousands of lives.
Bill Gates himself talks a lot about reducing carbon footprint we make and yet he refuses to sell his collection of airplanes. He has A COLLECTION of them.
Using higher level language that requires more operations than assembler is not a thing to worry about when talking about climate change. Especially without taking into account how much pollution have those managed to reduce by smartly controlling irrigation and other processes.
Many of these have C-bindings for their libraries, which means that slowness is caused by bad code (such as making a for loop with a C-call for each iteration instead of once for the whole loop).
I am no coder, but it is my experience that bad code can be slow regardless of language used.
Bad code can certainly be part of it. The average skill level of those coding C/C++/Rust tends to be higher. And modern programs typically use hundreds of libraries, so even if your own code is immaculate, not all of your dependencies will be.
But there’s other reasons, too:
And when working with multiple threads in Java, it is considered best practice to always clone memory of basically anything you touch. Like, that’s good code and its performance will be mediocre. Also, you better don’t think about using multiple threads in Python+JS. For those two, even parallelism was an afterthought.
Well, and then all of the above feeds back into all the libraries not being performant. There’s no chance to use the languages for performance-critical stuff, so no one bothers optimizing the libraries.
As someone used to embedded programming, this sounds horrific.
Yep. I used to code a lot in JVM languages, then started learning Rust. My initial reaction was “Why the hell does Rust have two string types?”.
Then I learned that it’s for representing actual memory vs. view and what that meant. Since then I’m thinking “Why the hell do JVM languages not have two string types?”.
I’m not a java programmer, but I think the equivalent to str would be char[]. However the ergonomics of rust for str isn’t there for char[], so java devs probably use String everywhere.
Java is still significantly faster and more efficient than Python tho - because it has ahead-of-time optimizations and is not executing plain text.
Idk numpy go brrrrrrrrrr. I think it’s more just the right tool for the right job. Most languages have areas they excel at, and areas where they’re weaker, siloing yourself into one and thinking it’s faster for every implementation seems short sighted.
At it’s heart, numpy is C tho. That’s exactly what I’m talking about. Python is amazing glue code. It makes this fast code more useful by wrapping it in simple® scripts and classes.
Faster, sure. Efficient, fuck no. With Java you have to run around and write ton of boiler plate code to do something simplest in nature.
I’m mainly talking efficiency in terms of energy use. I won’t deny that some ugly decisions have been made with Java :D
Energy use? That’s a pointless metric. If that is the goal then whole idea of desktop should be scraped. Waste of memory and hard drive space. Just imagine the amount of energy wasted on booting GUI.
Have you ever heard of datacenters, portable devices or climate change?
If you want to talk about climate change then electronics is the wrong place to point the finger at. For start look at cement manufacturing. It requires huge amounts of energy to produce even though we have eco-friendly variants ready to go. And cement production amounts to 8% of all greenhouse gasses released annually.
Hell, just ban private jets and you’ve offset all of the bad things datacenters ever made. Elon had 10 minute flight to avoid traffic which consumed around 300l of fuel. Royal family makes so many flights a year that you could go into the wild and eat bark until the rest of your life and you wouldn’t be able to offset their footprint in thousands of lives.
Bill Gates himself talks a lot about reducing carbon footprint we make and yet he refuses to sell his collection of airplanes. He has A COLLECTION of them.
Using higher level language that requires more operations than assembler is not a thing to worry about when talking about climate change. Especially without taking into account how much pollution have those managed to reduce by smartly controlling irrigation and other processes.
Python is the slowest (widely used) language there is. It’s not hard to be faster.
At least with Java, its the over(ab)use of Reflections and stuff like dependency injection that slows things down to a crawl.