python 3.12 was ALMOST javascript 

I think you may be thinking of Ryan Dahl from his 2018 JSConf talk "10 Things I Regret About Node.js": "What I've come to learn now that I'm aging is that whenever you're designing a program, there's things that you think might be cute to add in, you always regret those... don't do them!"

JS fails the most because of poor choices when adding a new feature and not being able to remove them in the future because it could potentially break some 20 year code on a website nobody visits anymore. Back when js was being designed dynamic languages where all the fuss, everybody wanted to use them. Everybody hated static types, they wanted everything to be determined at runtime with no safety checks whatsoever. The creator wanted to make the developer's life easier, that's why every number is a float and you can compare strings with numbers without any annoying conversions, because that's surely never going to cause any problems in the future. There is also the 'null' and 'undefined' which are basically the same but not the same at the same time. Now things have changed and statically typed languages like rust are getting popular.

Almost all of problems with JavaScript(which are a lot) comes from its original version. Newer features are generally well thought through

and python doesn't?

If it adds a little context, JavaScript was written in 10 days and was supposed to be an implementation of LISP/Scheme in the browser. It only has C-like syntax because Brendan Eich's boss at Netscape told him to give it Java syntax. Hence why the language's name changed at some point from LiveScript to JavaScript (though now its name is technically ECMAScript or ECMA262). I think there was also almost a lawsuit over that. But one area in particular where the Scheme influence really shines through is in the prototype system and the way it implements object-oriented inheritance through these meta-objects rather than classes like how Java does it. This very much resembles LISP and LISP-like languages because of how it lets you essentially redefine large parts of the language.

THIS

+1 for coming from R, and being happy, and then going to pandas and being confused.

pandas is the very library I always need to look up for everything before every time I use it. The syntax is so unique and the error message is so arcade. I has always been trying to avoid it except for simple table display in notrbooks.

that's why I use polars😂

@@yeelam4291 Yes, but polars has it's own issues. Mainly that they want to stop you from doing row access by indexing. Just stupid.

python 3.12 broke matplotlib: ru-vid.comYkZxLanqWmI?feature=share

Why was HATEOS a toy? BTW the HAL Google group is still going.

@@neildutoit5177 nah, my tooling around it was the toyish thing. HATEOS is a great idea with the worst possible marketing. Anyway the punchline was really that my bespoke solutions have always also been named AttrDict. It’s an obvious thing to want, when ya want it! 😇

agree, great catch - i hadn't even noticed this was trying to sneak into 3.12!

There's also AttrDict for when you actually want this semantic, a super common and short library .. oh wait was that literally the exact same thing getting added in here?

Same for me. Also, if you have tables with familiar columns, where you control the name, the difference between "structured object" and "unstructured container" gets blurry. To me, the video is a bit too doctrinal. nevertheless, AttrDict is something that shouldn't belong to json in the same way as SimpleNamespace doesn't belong to argparse. It should both be in dataclasses or collections.

If you work on tables with a familiar set of columns and you have control over the naming on a regular basis: The line between "structured object" and "unstructured container" gets blurry. Also in terms of convenience: To me it's highly understandable, to replace the hundreds of clunky [""] with a simple dot. Especially if you're not on an English keyboard and typing the brackets forces you to leave the main typing position for your fingers.

For debugging or rapid prototyping in notebooks I use dot notation, for finalized code I use brackets. Another pitfall of dot notation is that you cannot assign with it

c# has the advantage that there's a compilation step and a smart compiler to influence all of that. unfortunately python's roots are in scripts so its "module system" (and I call it that loosely) is really just a bunch of side-effects and a mega-global (sys.modules). a lot of scripting languages have basically the same problem I wish it weren't so -- but I don't see a good way to fix it without greatly limiting what you can do at the "module scope" and making it more difficult for scripting

enum also suffers from the "not enough maintainers" problem and has quite a few weird quirks in terms of the object model. the non-identifier attributes of enum are also kinda problematic -- I'm currently trying to fix a bunch of usages at work. imo it shouldn't have `__getitem__` and just let people use `getattr` if they need the weirdness

I believe also causes problems for how Python does generics now, if there were ever a desire to make that work with Enum. The Enum metaclass implements __getitem__, so Generics would be a behavior change.

indeed -- it only allowed for valid identifiers -- everything else still had to go through key notation

Clickbait.

The 'json' module in Python sucks, it cannot deserialize JSON into a class or a dataclass. For that you need third-party libraries.

@@fred.flintstone4099 Wouldn't be too much of an effort to add a to and from json method to the dataclass module. A way better approach to this problem imo.

@@gardnmi There is the `dataclasses-json` package that does that. Maybe they can add that... (would be very useful; not having auto-deriving these impls is.. not very scripty)

Or pydantic. Which has dict() and json() methods.

hah -- they are NOT friendly I've just moderated away ~100 very nasty comments

I use (and maintain) deadsnakes

@@anthonywritescode it seems deadsnakes is not supported on mac. is that correct?

yep -- just on ubuntu. I don't really use a mac all that often

I would like to hear your opinion on polars or any other good libraries that implement "data frames" in a proper way.

I think mojo is closed source because it's a vaporware PR stunt

I guess the biggest mistake of mojo is, that it's a superset of python and not a subset. Superset introduces totally pointless new syntax and forces separation instead of a steady progress of the whole python universe.

@@anthonywritescode true

this line is horrendous: hook = lambda mapping: namedtuple("foo", mapping.keys())(*mapping.values())

gods or fallen angels?

hadn't heard anyone had a less than positive opinion on Raymond.... (was sad to see it was him though) definitely an oversight/ too assuming on his part but you aren't contributing unless you make a few mistakes along the way. especially a feature we straight up don't need. Thank god for roll backs.

not my story to tell but there's some really problematic things that raymond has done and personally I've not had a positive interaction with them

@@anthonywritescode oh i see. eek. Thats unfortunate to hear. My interaction is highly limited. Always a shame to hear the quality of character of someone youve learned a lot from being problematic.

I never hat a personal interaction with Raymond, but his talks "writing Idiomatic code" and "python class toolkit" were very inspirational

then use a parsing layer to get structured data!

@@anthonywritescode whilst that is the "proper" way. A parsing layer would add more inconvenience (clutter) and would probably lend itself better to large code blocks.

there's plenty of space on pypi for such a bad idea -- but it does not belong in the standard library

@@anthonywritescode that's assuming you even can access pypi tho (because your project manager is doing the right thing and vetting dependencies, or simply because you are behind a corporate proxy, and are only allowed vanilla python)... And I still can't see why it's an issue if it's not even enabled by default

perhaps you missed the whole part of the video about maintenance and surface area? cpython already suffers from "not enough maintainers" and adding more junk that most people should not use is going to make that worse even if you can't access pypi it's trivial to copy the ~5 line recipe or use the already-existing alternative if you want to shoot from the hip. or you can use a real data serialization layer instead of a hack

@@anthonywritescode That's a +241/-1 patch. I've seen worse in terms of maintenance burden. Especially so when if it's going to be 100% unused in your opinion, so raising 0% of bug reports. Well, I guess that's fair if the actual part is 5 lines, that's a file I can easily copy from GitHub and import manually (which is what I do at my job, because no pypi). But I still can't use a "real data serialization layer", nor does I want to. I'm not going to write 3k lines of DTO just to transform my JSON into a CSV that I can email to someone who doesn't even need to know what Python is, because they are business workers, not IT. It looks like you don't want to understand that people might use Python as a *scripting* language. Where it's one of the most convenient, because it provide those kind of tools out of the box. I might be wrong, but I assume you also think that duck typing is a bad idea ? And that being able to monkey-patch objects is dumb ? Because Python here is ***GREAT***. Where writing a complete application is NOT the end goal. Some people just writes code that needs to work once or twice then they throw it away. Is using AttrDict on a full-blown app a bad idea ? Sure, but for a "just once app", this feature could be great.

@@COLAMAroro 200 LOC that includes new APIs is a maintenance burden, especially for codebases used by millions of people and kept alive by volunteer labor

I think Python is a great language for non-developers, for laymen, for scientists, tinkers, mathematicians, biologists, physicists, doctors, mechanics, and others who are not programmers but may need to write some code. It is good for small scripts. For professional developers I think Python sucks.

@@fred.flintstone4099 That's basically my stance on it as well. I think it's great for when you have a basic job that needs to be done. I think one of the issues is the horrible performance. It's not a big issue for smaller scripts that you just run, they complete and you get the result from a file or db inside your main system, your system might use more resources than necessary, but it's not like it matters too much. However, when everything is Python, it's really noticable.

​@@fred.flintstone4099 As a scientist, I can say that I still dislike Python. Modeling anything that requires 10 files starts becoming a huge mess. Think of things like machine dynamics, fluid simulations, computer graphics, chemical synthesis.

maybe you missed most of the video but the feature itself is a problem too

to be clear I am not doing that. data scientists have different goals that don't always require the same level of reusability and structure when exploring problems

that is my point actually. this is the standard library not the language

"I've been lazy a lot so trust me it's good actually"

pandas python behaving different than cpython python is weird and bad

% python3 -m this

Would it not be df['col1'] = (df['col2']+df['col3'])/5? Seems just as clean to me.

@@aznpwnsalot Yes it does. But somehow I still prefer df.col and it does not bother me. Maybe I have worked too much on pandas to know the difference. When I think about a dataframe df, it does not appear to me as "just another python object". I find naming a column "sort" far worse than, pandas ambiguous outcome of `df.sort` in that case.

Good point. The basics of Python are good, and Python is good for when using the basic things in it, but for more advanced stuff it sucks. It is great for non-developers because, but for professional developers it sucks.

I used to feel that way but decided to dig in and use it for some 'resume driven development'. And now I quite like it. Some things drive me mad, and I can't think why people consider it a 'simple' language - it's insanely complicated and has all sorts of footguns. But it is pretty good to code with if you have a good IDE and use type hints. 3 years ago I would have unconsciously chosen java to write just about anything other than firmware. Now I automatically choose python unless there's a good reason not to. Plus everything is JSON now so python's dicts are awesome. The pandas API is a shocker. I can never do the simplest thing with it without looking at the docs and SO, and I use it every few months.

so let me understand your point of view here: you're saying that because a programming language can do anything then garbage should be in the stdlib?