Free-threaded CPython is ready to experiment with!
Free-threaded CPython is ready to experiment with!
An overview of the ongoing efforts to improve and roll out support for free-threaded CPython throughout the Python open source ecosystem
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The only interpreted language that can compete with compiled for execution speed is Java
"Interpreted" isn't especially well defined but it would take a pretty wildly out-there definition to call Java interpreted! Java is JIT compiled or even AoT compiled recently.
it can be blazingly fast
It definitely can't.
It would still be blown out of the water by similarly optimized compiled code
Well, yes. So not blazingly fast then.
I mean it can be blazingly fast compared to computers from the 90s, or like humans... But "blazingly fast" generally means in the context of what is possible.
Port component to compiled language
My extensive experience is that this step rarely happens because by the time it makes sense to do this you have 100k lines of Python and performance is juuuust about tolerable and we can't wait 3 months for you to rewrite it we need those new features now now now!
My experience has also shown that writing Python is rarely a faster way to develop even prototypes, especially when you consider all the time you'll waste on pip and setuptools and venv...
"Interpreted" isn't especially well defined but it would take a pretty wildly out-there definition to call Java interpreted! Java is JIT compiled or even AoT compiled recently.
Java is absolutely interpreted, supposing that the AoT isn't being used. The code must be interpreted by JVM (an interpreter and JIT compiler) in order to output binary data that can run on any system, the same as any interpreted language. It is a pretty major stretch, in my mind to claim that it's not. The simplest test would be: "Does the program require any additional programs to provide the system with native binaries at runtime?"
It definitely can't.
Well, yes. So not blazingly fast then.
I mean it can be blazingly fast compared to computers from the 90s, or like humans... But "blazingly fast" generally means in the context of what is possible.
I find that context marginally useful in practice. In my experience it is prone to letting perfect be the enemy of good and premature optimization.
My focus is more in tooling, however, so, might be coming from very different places. In my contexts, things are usually measured against existing processes and tooling and frequently on human scale. Do my something in 5 seconds that usually takes a human 15 minutes and that's an improvement of nearly 3 orders of magnitude.
My extensive experience is that this step rarely happens because by the time it makes sense to do this you have 100k lines of Python and performance is juuuust about tolerable and we can't wait 3 months for you to rewrite it we need those new features now now now!
You're not wrong. I'm actually in the process of making such a push where I'm at, for the first time in my career. It helps a lot if you can architect it so that you can have runner and coordinator components as those, at their basics, are simple to implement in most languages. Then, things can be iteratively ported over time.
My experience has also shown that writing Python is rarely a faster way to develop even prototypes, especially when you consider all the time you'll waste on pip and setuptools and venv...
That's... an odd perspective to me. Pip and venv have been tools that I've found to greatly accelerate dev setup and application deployment. Installing any third-party dependencies in a venv with pip means that one can
pip freezelater and dump directly to a requirements.txt for others (including deployment) to use.Pip and venv have been tools that I’ve found to greatly accelerate dev setup and application deployment.
I'm not saying pip and venv are worse than not using them. They're obviously mandatory for Python development. I mean that compared to other languages they provide a pretty awful experience and you'll constantly be fighting them. Here's some examples:
- Pip is super slow. I recently discovered
uvwhich is written in Rust and consequently is about 10x faster (57s to 7s in my case). - Pip gives terrible error messages. For example it assumes all version resolution failures are due to requirements conflicts, when actually it can be due to Python version requirements too so you get insane messages like "Requirement foo >= 2.0 conflicts with requirement foo == 2.0". Yeah really.
- You can't install multiple versions of the same dependency, so you end up in dependency resolution hell (depA depends on foo >= 3 but depB depends on foo <= 2).
- No namespace support for package names so you can't securely use private PyPI repositories.
- To make static typing work properly with Pyright and venv and everything you need some insane command like
pip install --conf-settings editable-mode=compat --editable ./mypackage. How user friendly. Apparently when they changed how editable packages were installed they were warned that it would break all static tooling but did it anyway. Good job guys. - When you install an editable package in a venv it dumps a load of stuff in the package directory, which means you can't do it twice to two different venvs.
- The fact that you have to use venvs in the first place is a pain. Don't need that with Deno.
There's so much more but this is just what I can remember off the top of my head. If you haven't run into these things just be glad your Python usage is simple enough that you've been lucky!
I’m actually in the process of making such a push where I’m at, for the first time in my career
Good luck!
Oh my. Yeah. I have seen these before indeed. IMO, that's also a sure sign that a compiled language needs to come into the picture (port the simplest conflicting component). Especially if, for some reason multiple dependency versions are needed (I have hit that in particular myself).
I've not yet had the pleasure of working with Rust much but that's the target for the next version that we start, so, will be fun.
Rust is a lovely language if you're okay getting deep into the nuts and bolts.
- Pip is super slow. I recently discovered