Was there not, at some point, a disagreement among the emacs developers about how this conference was being managed?
As an aside, emacs has so much potential, I'm so glad the community continues to thrive. I use emacs exclusively for science data analysis and consistently impress my colleagues with how quickly things can be accomplished. If rough edges were polished in some of the python corners there could easily be an emacs renaissance in academia, a la nicolas rougier et al.
For just how popular python is in science now, the workflows are abysmal at best. 2 out of 3 of my colleagues won't touch it because Anaconda makes no sense, a command line work flow is too obtuse, and Matlab for all its disgusting nature is at least "natural" to work with as an environment in some sense. Which makes me sad. I have dreams that emacs makes that more approachable.
In any complex field, say data science or software development, any newcomer perceives the solutions to problems they still don't have as unnecessary complexity. So for example the whole idea of dependency management, environments or version control will get in their way. Because it's not yet their problem. They are solving simpler problems: how I run this simple script (or with Emacs, say, undo this change, etc...). In that regard Matlab excels at making it easy for newcomers and harder later.
We need gradual complexity, but I think it's very hard to design. It needs knowledge + didactic capability.
Honestly I've never understood Python for data analysis. R and Matlab have way better environments. R Studio is quite possibly the best environment I've ever used, in any language. Even creating C++ modules with Rcpp is easy. Julia is also getting there with a lot of natural advantages over R, Matlab or Python. I just don't get why anyone uses Python in this domain.
Python proper is terrible for analyzing data at scale.
It's the numpy, scipy, jupyter tools, as well as Anaconda, that make the sale.
Too, it's not just the analysis, but the extract/transform/load (ETL) beforehand. Python's general purpose wealth of tools had me transforming the FCC antenna coverage .zip[1] to shapefile and parking it in a spatialite file for QGIS in a relative jiffy.
Doubtless I could do all that in Julia or R, but I get to hone my python-fu at the office doing cloud stuff by day--another argument in favor of the general-purpose tool.
I argue that what makes the sale, is that that is what so many in the field are using. Not much inherent to the technologies, but you are taking on a daunting task if you want to compete with pytorch, instead of using it.
But we can assume people got on python/numpy stack because it brought some value compared to R. I'm not a big fan of numpy but I find it a bit shallow to think it's mostly follower effect at play. It might be though.. but that would be sad. Maybe Julia will bring balance back in the universe.
Matlab is awful at being a general-purpose language, anything that isn't wrangling matrices. Strings, paths, networking, etc are all really painful compared to Python or Julia.
Matlab was what came before Python. I do not ever want to go back. Sure, the Python ecosystem has its issues and Matlab has an IDE that is refined, but at least Python does have that ecosystem, all Matlab has is a shiny proprietary cage and littlr in the way of a cose sharing culture. Python being a proper language lets you break into other things, hookup completely unrelated code (and languages). All that's a giant pain in Matlab.
Not having access to a good R environment at work is one big reason.
At the company I work at there’s a pypi mirror with quite recent packages and it works out of the box - for R there’s only an ancient version and some hacks to get it to work with juptyer notebooks.
Just came here to plug Nicolas Rougier. He’s got some fantastic and very pretty-looking Emacs packages. He’s got good ideas of where Emacs should be in terms of usability in my opinion.
I have been a happy R + ESS (Emacs Speaks Statistics) user for a while now. I think ESS also supports python, I have no personal experience with that though. But I can agree that whenever I am forced to use Jupyter notebooks, it feel awfully unergonomic in comparison.
Strongly Agree! ESS is an incredible environment for statistical work, but I don't think it supports Python. There is some minimal support for Julia, but it's not quite as well supported as R.
Ah, looks like you are right and indeed ESS doesn't support python, a shame. As for Julia, I think a package that is shaping up to be interesting and along the same spirit is: https://github.com/gcv/julia-snail
This is interesting, I had the impression that notebooks were crossing this gap, are there specific command line issues that are a big bottleneck? Is it just better dependency management that's the big command line problem for example?
The Kindle talk sounds interesting: https://emacsconf.org/2021/talks/dashboard/ I have a an older Kindle hanging around that I'd be happy to get some new life out of with a little hacking.
I love the emacs philosophy. Doom emacs with evil mode is a gorgeous experience. However, once LSP and a few plugins are running it's just too slow to use. I hope one day we'll have a multi-threaded version of emacs that can compete with VSCode, JetBrains, and Xcode.
Do you use the native-comp branch of emacs? This probably doesn't make any difference when it comes to multithreading but it should make the experience a bit more smooth.
Isn't it time for everyone to move on to TeXmacs, not only for WYSIWYG editing of scientific/math documents, but also for note taking and even programming?
Yeah. I liked it when I used it, but it's not actually an emacs replacement in a general sense. There's a much smaller community and set of extensions (plug-ins in their term, packages in emacs). It was pleasant to use as a notebook front-end with Maxima and Octave when I used them.
TeXmacs is amazing but has been staying in a relative obscurity for some reason. It could be a great tool for the so-called literal programming. (Curiously, TeXmacs has little to do with TeX or emacs.)
To BeetleB's point, Emacs is free and open source software. I'm sure they wouldn't want to use a non free and open source network/streaming service to deliver the video.
Fair, I actually did assume that it costs money to put some videos up on twitch.
In other ways, though, I'm not actually clear that they lock you in much. Such that I'm not sure how it is any less free than most any other alternative.
Consider, it is basically the idea to use the town hall to host a local event.
except that its _not_ a public facility, and I dont see why we have to admit that kind of ambiguity just so that someone else can make a buck off of our work.
serving video is essentially free as in beer, and I'm pretty sure the FSF can afford to stand up a server.
i dont know why people are so eager to involve these services in their lives - i assure you, you can hold your own dick when you pee - its not that bad.
While town halls are public facilities, most rental halls are decidedly not. I think that was the point of the comment: If they were holding this event in person, would they refuse to do it in most facilities?
> i assure you, you can hold your own dick when you pee - its not that bad.
Comments like this are flamebait and, as an observer, quite unwarranted in this thread.
As an aside, emacs has so much potential, I'm so glad the community continues to thrive. I use emacs exclusively for science data analysis and consistently impress my colleagues with how quickly things can be accomplished. If rough edges were polished in some of the python corners there could easily be an emacs renaissance in academia, a la nicolas rougier et al.
For just how popular python is in science now, the workflows are abysmal at best. 2 out of 3 of my colleagues won't touch it because Anaconda makes no sense, a command line work flow is too obtuse, and Matlab for all its disgusting nature is at least "natural" to work with as an environment in some sense. Which makes me sad. I have dreams that emacs makes that more approachable.