All of our services we were our are significantly faster and more reliable. We used Rust, it wasn’t hard to do
The versioning issue I've seen across libraries that version change in many languages.
I don't tend to hit Python 2 issues using LLMs with it, but I do hit library things (e.g. Pydantic likes to make changes between libraries - or loads of the libraries used a lot by AI companies).
I also don’t have issues with quality of Python generated. It takes a bit of nudging to use list comps and generators rather than imperative forms but it tends to mimic code already in context. So if the codebase is ok, it does do better.
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.
But complaining about indentation is silly. Other languages' compilers don't require it like python does, but the humans using those languages all absolutely require proper indentation. Why not make it part of the language?
Except of course for those that did, Haskell, Fortran for example.
It’s pretty ok in Python, but meaningful indentation is amazing with a proper type system and compiler. Clean, consistent, efficient, and ensures working code is easily read and standardized.
I’m unaware of anyone accepting improperly formatted C# as ‘done’, and would reject any such PR out of hand because of the potential for legibility issues to hide bugs. So: if it were done when 'tis done, then 'twere well it were done by the compiler to save line noise.
"I don't think it makes much sense to try to add "functional" primitives to Python, because the reason those primitives work well in functional languages don't apply to Python, and they make the code pretty unreadable for people who aren't used to functional languages (which means most programmers). I also don't think that the current crop of functional languages is ready for mainstream." https://developers.slashdot.org/story/13/08/25/2115204/inter...
Ruby has `do … end` blocks that are readable and greatly improve the language, without turning it into a "functional" language.
I will never understand why people are upset about this.
You HAVE multi-line lambdas. They're called functions.
Yeah, I know you want a function that's only used once to be able to be defined in-line, but tbh I've always found that syntax to be pretty ugly, especially once you're passing two functions to a single call, or have additional parameters AFTER the function (I'm looking at you, setTimeout/setInterval).
If you mean "easy to get something out of it" then yeah, it's great.
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)
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.
I can see one way forward being to prototype them in python and convert.
We started in Python because of “the ecosystem”. It was a mistake. The amount of time we spend ripping out each dependency and pruning it to what we need is way higher than if we’d spent the month building out what we need. I miss compilers and LLMs will NOT generate config driven code or things that serde well. Everything has layers and layers of adapters by default and the domain model slowly erodes over time.
I've been using Claude Opus and it's pretty competent. I rarely have to make steering corrections. Once I had to deal with confusion, but, overall, the code is neat and the approaches sensible. It all depends on how much context you give it to work from, for instance. If it's building on top of a well organized codebase with a good best-practices document, it performs just fine.
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.
Yes it strains at the big to huge project end, not recommended to take it there. Still there are better tools to help now.
Choosing a language is a game of trade-offs: potentially slower execution in return for faster development time, for example. If your team is already familiar with Ruby, will asking them to write a project in Rust necessarily result in a better product? Maybe, but it will almost certainly take much longer.
Anyway, how many Python programs are actually "too slow"? Most of the time, Python is fast enough, even if heavy computation is offloaded to other languages.
As for Rust being the best language of them all, that's, like, your opinion, man.
That being said, I'm starting all new large development work in Rust. Python is hard to reason about due to its dynamic nature in large codebases. And if I'm enabling strict typing everywhere, I might as well use a typed language and get a performance boost. Obviously, this is only because I'm the sole developer and using AI to improve productivity.
Work settings are completely different and one has to be a team player to find the language that works for everyone.
Another classic lie about Python. The slower speed doesn't matter because it's development speed that's important, and Python gives you faster development speed!
Except... it absolutely doesn't. It would be very difficult to argue that Typescript has significantly slower development speed but it is much faster to execute. I also disagree that Python is any faster than Go, Rust or Lotion, but I think lots of people blindly accept that it is and would argue based on that.
At risk of nebulous repetition: There are many reasons one might choose a particular language. If you or your team find TypeScript or Go more amenable, by all means, use them.
The gotchas that I see with Python are that some really garbage code can work - that's more difficult in a language like Rust. The other nice thing about Python (aside from the fact that it can be very readable) is that devs rarely use threads and threads cause all sorts of race conditions - often when the performance of threading was never needed in the first place and the usage of them just added pointless complexity.
lol, no. Just no. Python is far superior for website backends unless perhaps you're running one of the top 20 websites in the world.
You can generate the HTML server-side using TSX. 100x better than anything Python offers.
That looks like HTML, but it's TypeScript. It gets compiled to actual HTML. Can any Python framework do that??
In Python, you'd typically write your logic in Python and your HTML in a separate Jinja2 template file — two languages, two files, context-switching. With Fresh + TSX, your logic and your markup live together in one .tsx file, both in TypeScript, with full type-checking throughout.
> That looks like HTML, but it's TypeScript. It gets compiled to actual HTML. Can any Python framework do that??
IMHO that's a terrible idea that no one should ever actually use, but if you are really in love with that, you can have it:
Not true, you can compile it to HTML on the backend or even statically too.
It's not a terrible idea; it's actually amazing. One of Typescript's best features. I do agree at first it seems icky (reminds me of Qt's MOC) but in practice it's fantastic. I recommend you try it before criticising. Python has nothing close (nor do any other languages tbf).
Yes, separating html out in jinja2 or whatever is far superior.
1. You can compose HTML using normal code - functions, loops, etc. No separate shitty template language or whatever.
2. You get full support for static typing and IDE code intelligence. That's huge and pretty much unique to TSX.
Once your program starts to get bigger you have abstractions that can cope fairly well and keep your code simple to use - this is what Perl didn't have.
If you need more speed then you can write extensions in some compiled language.I think TCL was better at this hybrid approach but Python is a nicer language in itself.
You can also just dump python and write everything in that other language but now you understand the problem space quite well and you won't be trying to learn about it using a language where change is "difficult."
- 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.
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).
Deleting "from my codebase" doesn't imply deleting it from history or backups. Just that the code isn't present for future edits or deployments.
The way you're talking, it sounds like you never delete code from your codebase. Do you just comment it out when you change a line to something else or replace a function with a new one? Just add new files?
I would need some evidence of that.
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.
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?
Our experiences differ then. Mine is that almost all of the code I write is directly targeted on the usually quite complex problem I am trying to solve. I don't do boilerplate, for example.
Just let me build a CRUD app, on the server, that spits out HTML without an excessive swamp of unmaintained nonsense and a cultish abhorrence of simplicity.
I personally chose C# for this reason, because ASP.NET is mature and (IMO) well designed. But there's also Java/Spring and and lots of other options in different languages depending on your preferences.
Not to mention that the demographic using Go - a simplistic-by-design, relatively slow GC'd language - is the last group I'd expect to get elitist about ORMs and demand every pound of performance from rawdogging SQL. That's a valid stance, but then why are you writing Go??! The common thread appears to be picking the most masochistic solution possible.
I can usually see the value of different languages for different use cases, but Go flummoxes me.
Had the rewrites not taken place, or Rust already being 1.0 by then, most likely would have had as many commercial success as Oberon and Limbo managed to.
You see this happening nowadays newer CNCF projects tend to be done in Rust, and there are even some that even go the C++ way, e.g. Envoy.
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)
Oh, that is such a nice thing.
The example:
>> 'hello'.toUpperCase()
Traceback (most recent call last):
...
AttributeError: 'str' object has no attribute 'toUpperCase'. Did you mean '.upper'?I really appreciate them going out of their way to do this, being quite aware of the hidden complexity in doing it.
Because the alternative is a rather sociopathic level of schadenfreude.
Example: to build our system, you run `mach build`. For faster rebuilds, you can do `mach build <subdir>`, but it's unreliable. AI agents love to use it, often get errors that would be fixed by a full-tree build, and will chase their tails endlessly trying to fix things that aren't broken. So someone turned off that capability by default and added a flag `--allow-subdirectory-build` for if you want to use it anyway. So that people would know about it, they added a helpful warning message pointing you to the option[1].
The inevitable (in retrospect) happened: now the AI would try to do a subdirectory build, it would fail, the AI would see the warning message, so it would rerun with the magic flag set.
So now the warning message is suppressed when running under an AI[2][3]. The comment says it all:
# Don't tell agents how to override, because they do override
[1] https://searchfox.org/firefox-main/rev/fc94d7bda17ecb8ac2fa9...
[2] https://bugzilla.mozilla.org/show_bug.cgi?id=2034163
[3] https://searchfox.org/firefox-main/rev/cebc55aab4d2661d1f6c2...
So when a library adds a new method, it silently changes which method client code calls? That's a bit too magic IMO. I think the best you can do is be case-insensitive and ban methods that differ only in case (or, if you want to extend the idea a bit more radically, ban having things in the namespace within Levenshtein distance x of each other, and then you can autocorrect errors smaller than x/2).
I was referring to the parent's statement "If a method or function call is similar enough to an existing one or a common one from other languages, to just have it silently use that." A compiler that substitutes a different function for the one I specified because it "knows what I really want" is horrifying.
It would help the writer once, but impose a cost on all future readers for the lifetime of the code.
It's a bit like reading English with bits of German, French and Russian. All of sudden you have to know that Buch, livre and книга all mean the same thing.
Not to mention that there are often subtle differences in meaning between words that on the face of it seem equivalent (in both human and computer languages).
It could be a nice feature for an IDE though, to help someone learn a language.
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.
> from __future__ import annotations (PEP 563) will continue to exist with its current behavior at least until Python 3.13 reaches its end-of-life. Subsequently, it will be deprecated and eventually removed.
Ironically, the new default behavior (making type annotation evaluation lazy) is not backwards compatible with the "from __future__ import annotations" behavior of converting annotations to strings, so they can't just rip out "from __future__ import annotations" and instead it needs to be deprecated and removed over multiple releases.
Oh, what tangled webs we weave! :-)
But this is a "...will continue to exist with its current behavior at least..." is an important bit there.
From pep-0749:
Sometime after the last release that did not support PEP 649 semantics (expected to be 3.13) reaches its end-of-life, from __future__ import annotations is deprecated. Compiling any code that uses the future import will emit a DeprecationWarning. This will happen no sooner than the first release after Python 3.13 reaches its end-of-life, but the community may decide to wait longer.
Check out symmetric difference
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.
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 ...
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.
There are ways to harden and/or reduce privileges, but shells/scripting languages will always have this issue on any modern OS.
The UNIX way to help prevent that is really to run processes as another user, but people seem to refuse to do so. You should always expect any process running as your UID to be able to access any data owned or visible to your UID.
While it is possible to reduce the risk of disclosure, they are all wack-a-mole preventions protecting the low hanging fruit, not absolute guarantees.
That is purely due to how UNIX works [0]
[0] https://man7.org/linux/man-pages/man7/credentials.7.html
And any app you run has access to $HOME, that's not a python specific thing. Look into apparmor or selinix if you want finer grained security
So for bleeding edge stuff it works out well or in places where documentation is not great like Apache Flink.
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)
>>> from collections import Counter
>>> c = Counter(a=3, b=1)
>>> d = Counter(a=1, b=2)
>>> c-d
Counter({'a': 2}) Several mathematical operations are provided for combining Counter objects to produce multisets (counters that have counts greater than zero). Addition and subtraction combine counters by adding or subtracting the counts of corresponding elements. Intersection and union return the minimum and maximum of corresponding counts. Equality and inclusion compare corresponding counts. Each operation can accept inputs with signed counts, but the output will exclude results with counts of zero or less.
> This is an unfortunate problem I've encountered many times, and it's often a problem for normal decorators too. But this has changed in 3.15, now the ContextDecorator will check the type of the function it's wrapping and ensure that the decorator covers the entire lifespan.
I very much like the idea of that change - but it also seems kind of dangerous, to do this with no "opt-in mechanism", as that quite subtly changes the behavior of existing usage sites.
This is a bit of a "spacebar heating" situation, because someone would have to intentionally use a decorator in the old, broken way, but if someone actually did that, things may unexpectedly break.
Lazy loading looks like a last nail in the coffin, where my love to Python was buried, although it was a long, tiresome process.
I still have a special place in my heart for the language and think it’s still got a niche.
It feels like a total waste of time and I wonder if other feel the same.
One of the consequences of the LLM tsunami might be the freezing of research and development in programming languages.
Maybe we'll be stuck with J's and python forever...
Who, then, understands the code? If the answer is "no one really", entropy will overwhelm your codebase sooner or later. Otherwise, you need to read the code, and for that the knowledge of language is still relevant.
I think about this on the regular -- I know the answer is currently "you own the code, so you have to understand it", but to unlock the true productivity multiplier, in the future, the answer has to be "no one really".
I think about it using the concepts from my job (academia) -- to actually have PhD student-level intelligence means that you have to trust that it does a good enough job that you can focus on other stuff. Professors often bring the correct ideas or intuitions, but they have to trust the PhD student to write the code and/or fill in the gaps in the proofs -- they can advise them on the high-level issues during a consultation, but that's about it.
I am pretty bad at working in the current LLM workflow -- it is tough for me to focus on reading a TCS paper for review, keeping all the details and invariants in my head, but every 5-10 minutes go to my PC, completely switch contexts/projects, read the code and think about the LLM's comments, suggest the next step, and then go back to reading.
I actually love this last feature !!