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@pradyunsg @henryiii Ah, maybe not so surprising, then. I feel like sometimes these, "We wrote it in <x> and now it's super fast!" projects are often "We approached this in a way that prioritizes performance and now it's super fast!"

In the best cases of this, you can import a lot of the performance gains into the original project. In the worst examples, the way they got the performance was by cutting corners, and the speed comparison is basically a lie.

Any chance `pip` can get some of the same performance benefits upstream (even if only on the "happy path" of hitting pypi.org?)

@henryiii This is honestly pretty shocking to me. I would have been confident that the bottleneck for `pip` was disk I/O and network latency, in which case rewriting in Rust would not really matter.

Is `pip` just slow now because of the resolver? Or is `pip` leaving a lot of performance on the table?

Also if someone has a better version of this please let me know I am not interested in maintaining any kind of shell code.

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Any experts out there have an idea why this function isn't working well with `ps`? If I pipe `df -h` into it, it works fine. If I redirect the out put from `ps -aux` to a file, then `cat` that file into it, it works. When I pipe `ps -aux` directly into it, I only get the header.

github.com/pganssle/dotfiles/p

@freemo That is actually a myth. I have played a lot of Minecraft recently and the actual rule is that if you fall into *water* you won't be hurt at all, no matter how shallow the water.

If you are working at high heights, it is best to keep a bucket of water on you in case you fall.

The Japanese version of Jeopardy! is basically exactly as I expected (though I didn't think they would have more than 3 contestants)

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(Note: I am watching a different episode than the one I linked)

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They seem a little looser with the rules, too. At one point there is a question about Batman where one contestant answers, "Poison Ivy" and the host is like, "No we want the actress" and the guy says, "Uma Thurman" and gets it right.

Later on no one buzzes in on one of the questions and after the host is ready to move on one guy tries to hit the buzzer and the host is like, "Oh hey you want to answer?" And the guy gives a response.

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In the late 90s there was a Mexican version of Jeopardy!, and for some reason they decided to add dancing girls to it: youtu.be/P0DUhx0avLw?si=9-eF21

I did not expect them to dance for quite so long at the beginning there...

@eric I remember the first time I saw them I was like, "Oh that is an interesting duck wait what the fuck is going on down there‽"

@Log3overLog2 I wonder if a generalization exists for N paper l parties? Can you start with 4N districts, have party 2 combine, then party 3 combine again?

I'm guessing no, since in the extreme case you have log2(population) parties, the "define" party is forced to define 1-person districts and is effectively left out of the process...

I've started a blog! This first post is a mixture of a "hello world" and a summary of what I'm thinking of next for PyO3 (hint: stronger community network).

polar.sh/davidhewitt/posts/hel

#rust #python #blog

there's been almost twenty years of work on optimizing javascript engines with JIT and complex heuristic-based GC and a wealth of feature-rich profiling and analysis tools and validation and testing frameworks for deployment and integration and syntax improvements and functional and higher-order primitives and serverside transpiled code. and it's all enabled some amazing new stuff, for example github now takes 10 seconds to display a plain text file, and you cant search properly anymore

@brainwane Oh I was half-joking anyway, but they don't care about the truth value of saying sample sentences because they don't think you should say sample sentences *at all*. The whole idea is that you listen to increasingly complex but naturally spoken language, and over time your brain learns the language, without output.

Eventually your brain has a solid model of the language and a broad vocabulary to call on, so when you start talking you basically have natural conversations rather than staged interactions where you ask about where the library is or whatever.

It's not a monolithic movement, but I do get the impression that a lot of CI proponents actually see it as a real feature that you are having normal conversations where you are talking about your own life and the things you want to know, and implicit in that is that the amount of "lying" you do is going to be roughly the amount of lying you do in your normal life.

@brainwane I have been learning Spanish with Dreaming Spanish last 6 months or so and I do sorta see where they are coming from on waiting to acquire a lot of the language before speaking. With ~400 hours of Spanish, I am comfortable enough understanding the language that I have noticed a bunch of things about the pronunciation and differences in accent that I am sure I would have to consciously change if I had been speaking from the start.

@brainwane The comprehensible input people apparently agree with you, since they think you basically don't talk at all until you basically know the language 😛

comprehensibleinputwiki.org/wi

@kevin I think the idea is that they are not going to make a second season, so the expectation is that the entire story will be told in 8 episodes or whatever, rather than just having a season end in a cliffhanger or dragged out for several seasons or whatever.

New version of DateType today, now supporting #Python 3.7+, thanks to a contribution from Maciek Olko: pypi.org/project/datetype/2024

(It's also the first release with the "5 - Production/Stable" Trove classifier, upgraded from "Development Status :: 3 - Alpha", if you care about such things.)

New post: harihareswara.net/posts/2024/t Whether And How To Trust A New Maintainer

What kind of trust does a project #maintainer need to have in a new co-maintainer? To get better at #opensource #sustainability, we need to improve at recruiting, training, & promoting new leaders.

I cover attributes to check for.

I mine 4 comparable situations for assessment ideas, & explain how to reduce how much trust you NEED to give by promoting someone.

&: 3 options if you're low on time

#maintainership #FLOSS

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