Python 3.15: features that didn't make the headlines

167

rrbanffy about 4 hours ago 74 commentsRead Article on blog.changs.co.uk

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Discussion (74 Comments)Read Original on HackerNews

kokada•about 4 hours ago

From this example:

    lazy from typing import Iterator

    def stream_events(...) -> Iterator[str]:
        while True:
            yield blocking_get_event(...)

    events = stream_events(...)

    for event in events:
        consume(event)

Do we finally have "lazy imports" in Python? I think I missed this change. Is this also something from Python 3.15 or earlier?

llimllib•about 3 hours ago

3.15: https://docs.python.org/3.15/whatsnew/3.15.html#whatsnew315-...

javcasas•about 2 hours ago

> When an AttributeError on a builtin type has no close match via Levenshtein distance, the error message now checks a static table of common method names from other languages (JavaScript, Java, Ruby, C#) and suggests the Python equivalent

Oh, that is such a nice thing.

kzrdude•about 1 hour ago

What benefit does the lazy import have here - if we use the value in a type hint at module scope anyway? Would that require Deferred evaluation of annotations -- which I don't think are enabled by default?

js2•28 minutes ago

Type annotations are lazily evaluated by moving them behind a special annotations scope as of 3.14:

https://peps.python.org/pep-0649/

https://docs.python.org/3/reference/compound_stmts.html#anno...

With 3.15, using lazy typing imports is more or less an alternative to putting such imports behind an "if TYPE_CHECKING" guard.

kzrdude•13 minutes ago

Ah, thanks for the update. My only check before asking was to check if the future feature for annotations had been enabled by default yet. It has then effectively been abandoned instead, I guess.

karpetrosyan•about 3 hours ago

Note that you can work around it by implementing `def __getattr__(name: str) -> object:` at the module level on earlier Python versions

saghm•about 2 hours ago

Somehow I have no trouble imagining this being used as a rationale to avoid unnecessary "magic" to the language for years

boxed•about 3 hours ago

Yes, 3.15+

rad120•about 3 hours ago

Python is such a weird language. Lazy imports are a bandaid for AI code base monstrosities with 1000 imports (1% of which are probably Shai Hulud now).

And now even type imports are apparently so slow that you have to disable them if unused during the normal untyped execution.

If Instagram or others wants a professional language, they should switch to Go or PHP instead of shoehorning strange features into a language that wasn't built for their use cases.

stingraycharles•about 3 hours ago

> Python is such a weird language. Lazy imports are a bandaid for AI code base monstrosities with 1000 imports

Just because you don’t like a feature doesn’t mean it’s because of AI and bad code.

xtajv•about 1 hour ago

Too much syntactic sugar causes cancer of the semicolon.

sigmoid10•about 3 hours ago

I think this is just a natural consequence of an easy-to-use package system. The exact same story as with node. If you don't want lots of imports, don't make it so damn easy to pile them into projects. I'm frankly surprised we still see so few supply chain attacks, even though they picked up their cadence dramatically.

tremon•about 1 hour ago

True, but this is yet another code path that isn't exercised until specific conditions happen. That means even more latent application behaviour can go undetected by unit testing and security profiling until the moon is in the right phase, which is a boon for submarine attacks.

novov•about 3 hours ago

Empirically, I have used the current accepted way to do lazy imports (import statement inside a function) before AI coding was even a mainstream thing, for personal code that sometimes needs a heavy import and sometimes doesn’t.

The lazy statement would be an improvement as it allows one to see all the imports at the top where you expect them to be.

afH12•about 3 hours ago

As a now deleted comment pointed out, lazy imports had been requested forever. They were rejected forever and were accepted just when BigCorps wanted them.

Python-dev now is paid to shore up the failed Instagram stack.

formerly_proven•about 3 hours ago

On most unix-likes all "imports" via shared libraries (e.g. in C / C++) are lazy by default.

JohnKemeny•about 3 hours ago

> I've left this one to the bonus section because I've never used set operations on Counters and I'm finding it extremely hard to think of a use case for xor specifically. But I do appreciate the devs adding it for completeness.

Check out symmetric difference

https://en.wikipedia.org/wiki/Symmetric_difference

qsort•about 2 hours ago

Yeah, but applied to counters it would be the symmetric difference between multisets, which doesn't have a natural definition. If I understood the proposal they'd be defining it as absolute value of the difference of the counts, which isn't even associative.

If they only considered parities it could be interpreted as addition in F_2, which is more natural, but I'd still agree that it's hard to see how you'd use something like this in practice.

brianwawok•about 4 hours ago

I was so into Python for 10 years, was enjoyable to work in. But have deleted 100k+ lines this year already moving them to faster languages in a post AI codebot world. Mostly moving to go these days.

stuaxo•about 3 hours ago

This is straightforward in the first instance, but how do you see maintenance of those projects going forward - especially adding more complex features ?

I can see one way forward being to prototype them in python and convert.

BOOSTERHIDROGEN•about 3 hours ago

Interested in why you'd use Python in the first place? Advice for someone who knows nothing about programming - what would you suggest?

IshKebab•about 2 hours ago

IMO the main reasons people use Python are:

1. The very first steps are quite simple. Hello world is literally just `print("hello world")`. In other languages it can be a lot more complex.

2. It got a reputation as a beginner-friendly language as a result.

3. It has a "REPL" which means you can type code into a prompt and it will execute it interactively. This is very helpful for research (think AI) where you're trying stuff out and want to plot graphs and so on.

IMO it is undeservedly popular, or at least was. Wind back 10 years to when it was rapidly gaining mindshare:

1. While "hello world" is simple, if you went further to more complex programs you would hit two roadblocks: a) the lack of static type checking means large programs are difficult to maintain, and b) it's really really slow.

2. While the language is reasonable, the tooling (how you install packages, manage the code and so on) was eye-bleedingly abysmal.

3. While the REPL did technically exist, it was really bare bones. It couldn't even handle things like pasting code into it if the code contained blank lines (which it usually does).

However since it has become arguably the most popular language in the world, a lot of people have been forced to use it and so it is actually getting quite decent now. It has decent static types (even if lots of people still don't use them), the REPL is actually decent now (this changed very recently), and there's a new third party tool called `uv` to manage your code that is actually good.

The biggest issue with it now is that it's still horrifically slow (around 50-200x slower than "fast" languages like C++, Rust etc). It is pretty unlikely that that will ever change. People always try to excuse this by saying Python is a "glue" language and you just use it to connect components written in faster languages, but a) that's pure "you're holding it wrong", and b) that only works in some cases where there are nicely separated "slow bits" that can be moved to another language. That's the case for AI for example, where it's all numerical, but for lots of things it isn't. Mercurial was a competitor to Git that was written in Python and lost partly because it was way too slow. They've started writing parts in Rust but it took them 10 years to even start doing that and by then it was far too late.

> what would you suggest?

It really depends on what you want to make. I would pick something to make first and then pick the language based on that. Something like:

* AI: Python for sure. Make sure you use uv and Pyright.

* Web-based games: Typescript

* Web sites: Typescript, or maybe Go.

* Desktop GUI: Tbh I'd still use C++ with QtWidgets. Getting a bit old-school now tbf.

Also Rust is the best language of them all, but I dunno if I'd pick it as a beginner unless you really know you want to get into programming.

mixmastamyk•1 minute ago

ptpython has existed for a decade+ and python is high level, more readable than most languages. Exec speed hasn’t mattered in my near thirty years of using it for business and prototyping tasks which it promoted early.

Yes it strains at the big to huge project end, not recommended to take it there.

sinpif•about 2 hours ago

I'm still on the lookout for a comprehensive Django-like web framework for go. That would be an instant hit for me.

pennomi•about 1 hour ago

Same here. Django is my last holdout for Python. Everything new is go.

physicsguy•about 3 hours ago

Go is terrible for scientific/ML work though, the libraries just aren't there. The wrapping C API story is weak too even with LLMs to assist.

Try and write a signal processing thing with filters, windowing, overlap, etc. - there's no easy way to do it at all with the libraries that exist.

LtWorf•about 3 hours ago

I think the purpose of go is to write CRUD. Stray from that and you're on your own.

deppep•about 3 hours ago

i don’t really see it this way. the value of a token in Python is much higher than it is in lower-level language

shankysingh•about 4 hours ago

Thats very intersting, If I may ask was it from professional projects or personal projects?

mountainriver•about 4 hours ago

Same, I’m not sure how Python survives this outside of machine learning.

All of our services we were our are significantly faster and more reliable. We used Rust, it wasn’t hard to do

prodigycorp•about 3 hours ago

the funny thing is that everyone, including myself, posited that python would be the winner of the ai coding wars, because of how much training data there is for it. My experience has been the opposite.

tyre•about 3 hours ago

I felt the opposite, because Python isn’t a great language. It won because of Google, fast prototyping, and its ML interop (e.g. pandas, numpy), but as a language it’s always been subpar.

Indentation is a horrible decision (there’s a reason no other language went this way), which led to simple concepts like blocks/lambdas having pretty wild constraints (only one line??)

Type decoration has been a welcome addition, but too slowly iterated on and the native implementations (mypy) are horribly slow at any meaningful size.

Concurrency was never good and its GIL+FFI story has boxed it into a long-term pit of sadness.

I’ve used it for years, but I’m happy to see it go. It didn’t win because it was the best language.

rplnt•about 2 hours ago

AI benefits from tools to verify its halucinations. That's much easier in a typed and compiled language. Then have a language that can't be monkey patched at runtime and the confidence increases even more.

If you mean "easy to get something out of it" then yeah, it's great.

dkersten•about 2 hours ago

Typescript wins in terms of training data IMHO, by which I mean that the training data is large enough that AI does great with TS, and the language is (IMHO) superior to Python in many ways.

I personally now use a mixture of Typescript and Rust for most things, including AI coding. Its been working quite well. (AI doesn't handle Rust as well as TS, in that the code isn't quite idiomatic, but it does ok)

lexicality•about 3 hours ago

a lot of the training data is either for python 2 or just generally very low quality

lsbehe•about 3 hours ago

The tons of python code would be great training data if there was any consistency across the ecosystem. Yet every project I've touched required me to learn it's unique style. Then I'd imagine they practically poisoned half the training set because python2 is subtly different.

LtWorf•about 3 hours ago

You can test on the device directly, without needing to recompile to try something.

zabzonk•about 3 hours ago

Three things I find unlikely about this:

- You wrote 100K lines of code (I've worked on several large C++ projects that were far smaller)

- You wrote those lines in Python (surely the whole point of Python is to write less code)

- You deleted them (never delete anything, isn't this what modern VCS is all about?)

But whatever floats your boat.

dkersten•about 2 hours ago

> You deleted them (never delete anything, isn't this what modern VCS is all about?)

The person said: "deleted 100k+ lines this year already moving them to faster languages"

Are you saying that when you move code to another language/rewrite in another language, you leave the original languages code in your repo?

They didn't say they deleted it from their git history. I delete code all the time (doesn't mean its "gone", just that its not in my git head).

zabzonk•about 2 hours ago

Well, they deleted it from somewhere. As I assumed they were using a VCS I assumed they deleted it from that. Or are they really short of disk space?

throwatdem12311•about 2 hours ago

100k lines is tiny what are you on about, especially in the monolithic app sass world where many Fyll stack apps that handle all business ops are probably written with Django.

Our entire business runs on 300k lines of Ruby (on Rails) and I can keep most of the business logic in my head. I would say our codebase is not exactly “tiny” and just cracking the ceiling into “smal” territory. And comparatively, people probably write even less code in equivalent rails apps to django ones. 100k lines of C++ is miniscule.

Obviously “deleting code” in this context doesn’t mean purging version control history but the current state of the codebase.

zabzonk•about 2 hours ago

> 100k lines is tiny

No, no, it is not, or at least not in my experience (I do not and never have done web development - medium performance C++ code - I don't see how I could write, understand and support 100K lines of code in this area).

And so, what does your Ruby code actually do?

squirrellous•about 2 hours ago

Uhm what? All of those things are totally ordinary.

zabzonk•about 2 hours ago

> All of those things are totally ordinary. reply

I would need some evidence of that.

kwon-young•about 1 hour ago

It's nice that python 3.15 added Iterator synchronization primitives: https://docs.python.org/3.15/library/threading.html#iterator.... These will nicely complement my threaded-generator package which is doing just this but using a thread/process+generator+queue: https://pypi.org/project/threaded-generator/

armanj•about 1 hour ago

funny how we may have to wait even longer for llms to pick up this update in their pre-training

sunshine-o•about 2 hours ago

I am not a python dev but have the utmost respect for the ecosystem.

But damn, with all the supply chain attacks now in the news, could they just make a simple way (for non python insiders) to install python apps without fearing to be infected by a vermin with full access to my $HOME ...

surajrmal•about 1 hour ago

There is little that they can do short of running the programs in a VM. Linux distros aren't engineered to consider applications as something different from the user running them. You need a completely different security model to achieve that and the Python runtime isn't tackle that.

sunshine-o•1 minute ago

In its inception 35 years ago the creator of python could not foresee how far python would go and how the environment would look like today. But nowadays there are a lot of security mechanisms they could leverage to adapt (from chroot by default to namespaces, cgroup, etc. on Linux, pledge, unveil on OpenBSD).

The very idea that you offer a (python) package installer that is gonna pull a tree of code published and updated by random people in an unvetted manner open the door to all the supply chain attacks we are seeing.

Around the same time (early 90s) Java was designed with high isolation in mind but the goal and vision was very different. And Java had its own problems.

I'm saying that because at some point the security problem is gonna really hurt the python ecosystem.