When people deploy python and perl code, they have to either export their entire environment, or build a container. The latter is not possible in a number of deployment cases, and the former carries all manner of dependency radius gotchas.

So I am building (ok, I am prompting/testing/reviewing, the agent is doing the heavy lift) compilers for each of python 3.14.x [1] right now, and perl 5.42.x [2], that can generate static code.

Early stages, perlc does work well, pyc is a work in progress.

[1] https://github.com/joelandman/pyc

[2] https://github.com/joelandman/perlc

Comments URL: https://news.ycombinator.com/item?id=46412531

Points: 3

# Comments: 3

I am not sure if this is a server side thing at Microsoft, or a problem with the application itself. True under Windows, Linux, via local app, and via the web app.

For larger meetings (> 50 people), we use zoom. Unlike teams, zoom generally just works. Quite well in fact.

Teams is simply crap software, forced upon us. If we could jettison that and Outlook, I would be grateful. Though our IT looks at us in an unblinking stare, if we ask them to allow us to use any of the better clients on mobile, laptop, desktop, windows or linux. Its almost as if our third eye in the middle of our forehead opened up.

A rule of thumb I use for cooling is, you can rarely have too much. You should over-engineer that aspect of your systems. That and the power supply.

I have a 7950x, with a water block capable of sinking up to 300W. Under heavy load, I hear the radiator fans spinning up, and I see the cpu temp hover around 90-93 C. That is ok, though cooler would be better. My next build (this one is 2 years old) will also use a water block, but with a higher flow rate, and a better radiator system. I like silent systems, though I don't like the magic smoke being released from components.

Years later, Ewald and others had a hand in destroying the Beast and Alien CPUs in favor of the good ship Itanic (for reasons).

IMO, Ewald went from company to company, leaving behind a strategic ruin or failure. Cray to SGI to Linux Networx to ...

    joe@zap:~ $ julia
                   _
       _       _ _(_)_     |  Documentation: https://docs.julialang.org    
      (_)     | (_) (_)    |
       _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
      | | | | | | |/ _` |  |
      | | |_| | | | (_| |  |  Version 1.10.5 (2024-08-27)
     _/ |\__'_|_|_|\__'_|  |
    |__/                   |

    julia> z=1+2*im
    1 + 2im

    julia> z*conj(z)
    5 + 0im

    julia> sqrt(z*conj(z))
    2.23606797749979 + 0.0im

    julia> abs(z)
    2.23606797749979

Definitely not a dead language. A mature and stable language, which won't surprise you.

[1] https://www.activestate.com/products/komodo-ide/

My c code from 1996 requires rework. My C++ code from 2014 requires rework (I had to do this with others code as well to use a std capability). Python code rarely survives 3.6 -> 3.12 never mind 2.7 to 3.x. I worked at a company that had (very unwisely) written a massive part of its infrastructure in Py2.7, and was using it a decade past its expiration date.

Perl just works.

DataFrames.jl, DataFramesMeta.jl, and the rest of the ecosystem are outstanding. Very similar to pandas, and much ... much faster. If you are dealing with small (obviously subjective as to the definition of small) dfs of around 1000-10000 rows, sticking with pandas and python is fine. If you are dealing with large amounts of real world time series data, with missing values, with a need for data cleanup as well as analytics, it is very hard to beat Julia.

FWIW, I'm amazed by DuckDB, and have played with it. The DuckDB Julia connector gives you the best of both worlds. I don't need DuckDB at the moment (though I can see this changing), and use Julia for my large scale analytics. Python's regex support is fairly crappy, so my data extraction is done using Perl. Python is left for small scripts that don't need to process lots of information, and can fit within a single terminal window (due to its semantic space handicap).

I'm not much worried about this specific example of information exfiltration, though I have significant concerns over how one may debug something like this for applications working with potentially more sensitive data than email signatures. Put another way, I think we are well within the infancy of this technology, and there is far more work needed before we have actually useful applications that have a concept of information security relative to their training data sets.

2: Minimally. I was asked for the reason for my departure, and I was transparent as I could be, indicating what I knew and the circumstances. People were curious about it, but then again, its not relevant to finding new work. I will say that I found that multiple potential employers concluded successful interviews with unrelated programming tests. It felt like a set of coffin problems[1], that older folks like me, not trained in CS, but writing code for 40+ years, would not do well on.

This is a huge red flag. I actually had someone tell me that I 'needed to know how to program' to do the job I'd applied for, even though I have a public documented history of programming and software development/engineering, have developed and shipped code for decades, for research, products, patches, ...

That impacted search a bit.

3: There's not much of a stigma these days. Your self worth is not tied up in your job. Your value isn't either. You can take time to decompress, retool, think, train, research.

Put another way, if an employer thinks its a problem, you might want to steer clear of that employer. Bring the conversation quickly to a close, amicably, so you don't waste time and create bad feelings.

On jobs in general, employers generally are their to please and profit their owners. Understanding all their actions in terms of this (HR is there to protect the employer, etc.) can help you separate your sense of self worth from the position or company.

[1] https://www.reddit.com/r/math/comments/gxpoyo/soviet_coffin_...

If you are running a large SaaS this might not be the right package for you. But if you are putting together a small site (blog, single page webapp, etc.) this is a great, simple, and easy to deploy tool.

Well, no. This is python's strategy. Doesn't make it the winning strategy. Python implicitly forces multiple languages upon you. A scripting one, and a performance one. Meanwhile languages such as Julia, Rust, etc. allow you to do the work in a single (fast/compiled) language. Much lower cognitive load, especially if you have multiple cores/machines to run on.

Another point I've been making for 30+ years in HPC, is that data motion is hard. Not simply between machines, but between process spaces. Take large slightly complex data structures in a fast compiled language, and move them back and forth to a scripting front end. This is hard as each language has their own specific memory layout for the structures, and impedance matching between them means you have to make trade-offs. These trade-offs often result in surprising issues as you scale up data structure size. Which is one of the reasons that only the simplest of structures (vectors/arrays) are implemented in a cross language scenario.

Moreover, these cross language boundaries implicitly prevent deeper optimization. Which leads to development of rather different scenarios for code development, including orthogonal not-quite-python based things (Triton, numba, etc.).

Fortran is a great language, and as one of the comments pointed out, its really not that hard to learn/use. The rumors of its demise are greatly exaggerated. And I note with some amusement, that they've been going on since I've been in graduate school some 30-35 years ago. Yet people keep using it.

Something about the deep field and ultra deep field pictures that makes me happy. Also makes me wonder about how many beings in these other galaxies look out, see Milky Way colliding ever so slowly with Andromeda in their own deep field views.

As for notable things I've done, I worked on an experiment in undergrad, which won the PI (small group) the Nobel in physics in the late 90s, writing computer software for experiment control. That and getting a PhD in physics from a student of a student of a different Nobel laureate. I founded and ran my own company for about 14 years getting to millions in revenue with no external initial investment. I worked with my business partner to try to raise money to build accelerators for computing in 2002-2007 as I'd argued that they would be the dominant form of HPC in the mid 2010s. No investor would bite.

But sure. Ask me about high school. Not the 40 years since high school.

Canonical is a complete waste of time/effort. Ubuntu is a fine distro, but the hiring process is so completely flawed, as this article and many others (check out glassdoor, my interview is now up as well)

That someone (likely very senior) greenlit this process, signed off on it, and thinks it is successful enough to keep doing it, is a massive set of red flags about this company. The company reviews (not interviews) on glassdoor tell me the same story. Its like their employees have written a collective "WTF", and management is completely impervious, blissfully clueless, as to how broken, how disfunctional, their processes are. The implicit assumption in this is that if they were aware, they would adapt and change them. I do not believe this to be the case.

So, in summary, steer a wide path around this company. You don't need their crap. Maybe, eventually, they will get a clue. Though I think this would only happen when there is a materiel leadership change at the top.