I would vote for docker as well. The last time I had to inherit a system that ran on virtual machines, it was quite a pain to figure out how the software was installed, what was where in the file system, and where all the configuration was coming from. Replicating that setup took months of preparation.

By contrast, with Docker, all your setup is documented. The commands that were used to install our software into the virtual machines and were long gone are present right there in the Docker file. And building the code? An even bigger win for Docker. In the VM project, the build environment for the C++ portion of our codebase was configured by about a dozen environment variables, none of which were documented. If it were built in Docker, all the necessary environment variables would have been right there in the build environment. Not to mention the build commands themselves would be there too, whereas with VMs, we would often have developers build locally and then copy it into the VM, which was terrible for reproducibility and onboarding new developers.

That said, this all comes down to execution - a well-managed VM system can easily be much better than a poorly managed Docker system. But in general, I feel that Docker tends to be easier to work with than a VM. While Docker is far from flawless, there are a lot more things that can make life harder with VMs, at least from my experience.

Just in case this comment didn’t make it explicitly clear, you can just invoke the python binary inside your venv directly and it will automatically locate all the libraries that are installed in your virtual environment.

To show how this works, you can look at the sys.path variable to see which paths python will search for modules when you run import statements. Try running python3 -c 'import sys; print(sys.path)' using your system python, and you will only see system python library paths. Then, try running it again after replacing python3 with the full path to the python3 binary in your venv, and you will see an additional entry in the output with the lib directory in your venv, which shows that python will also look there for modules when an import statement is executed.

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This is quite cool. I always find it interesting to see how optimization algorithms play games and to see how their habits can change how we would approach the game.

I notice that the AI does some unnatural moves. Humans would usually try to find the safest area on the screen and leave generous amounts of space in their dodges, whereas the AI here seems happy to make minimal motions and cut dodges as closely as possible.

I also wonder if the AI has any concept of time or ability to predict the future. If not, I imagine it could get cornered easily if it dodges into an area where all of its escape routes are about to get closed off.

This is quite cool and a very interesting read. I’m not sure if it’s something I would want to use in a real project, because it looks like you’re basically inventing a new language within Python’s type system itself, which is a little weird. That said, I feel like I learned a lot from reading this, and it was a very interesting demonstration of what you can do with Python’s type-checking system.

There is no way to make a network request faster than a function call.

Apologies in advance if this it too pedantic, but this isn’t necessarily true. If you’re talking about an operation call that takes ~seconds to run, then the network overhead is negligible. And if you need specialized hardware for it, then it definitely could be delegate it out to a separate machine over the network. Examples could include requiring a GPU, more RAM, or even a faster CPU if your main application is running on more power-efficient CPUs.

I’m not saying that this is true in every case - they are definitely niche cases. But I definitely wouldn’t say that network requests are never faster than local function calls.

Agreed on all points. I think some of the issues that you’re facing are things that would be resolved if Ocaml were more popular. But some others would be harder to fix without making breaking changes to the language as I mentioned earlier. If I had to put it as succinctly as possible, I’d say that the language just needs a lot more polish which would probably happen if it were more mainstream. But not all languages have to be mainstream, and maybe Ocaml’s purpose in the world is, as you put it, to inspire other languages. It is definitely extremely good at that!

No one has said Ocaml yet, so I will. It’s not a perfect language, but it has a lot of cool ideas and concepts. It’s a functional language, but allows you to write imperative code when you want to. Algebraic data types and type matching are built natively into the language and work very nicely. It’s type inference capabilities are very powerful (though that can backfire at times), and the |> operator is really, really fun to use. It also has very powerful module/functor capabilities, though they go a bit over my head since I haven’t had a chance to play with them. Also, Opam is a very powerful package manager and it’s pretty easy to wrap/bind external libraries with it.

I’d love to see some improvements to the language - the syntax is a bit confusing and ugly at times (but this unfortunately can’t be fixed without breaking the language of course) - but overall I think I’d have a lot more fun programming in Ocaml than what I do in my day job.

My advice would be to learn C first (or at least develop a good understanding of it). It’s extremely important to understand how memory works in C so that you can understand pointers in C++; and also important to understand how functions work so you can understand classes and methods in C++. I would go through The C Programming Language. It’s fairly concise and while you don’t have to go through it cover to cover, you should at least understand the chapters on structs, pointers and functions (up to chapter 6, I believe).

(Note that the wikipedia link that I posted above has a link to the full text of the book in pdf format.)

The reason why I think it’s important to understand C is because when you learn C++, then you’ll understand how the language abstracts over a lot of the lower-level functionality in C. new in C++ supplants malloc in C for example, and your understanding of functions in C will map to more complicated concepts like constructors, destructors, copies, methods, and operators in C++. At this point, I would probably start learning how classes in C++ work. They’re basically structs with private member variables and methods defined in the scope of the class. learncpp.com, is the best reference that I’m aware of (it’s very thorough, which makes for a pretty slow read, but you’ll understand it very well). I would probably start with chapter 14 (introduction to classes), and then go back to the earlier chapters to fill in the gaps, but this is more dependent on how you think you learn best.

Be aware though, that if you don’t have existing experience with OO development, then C++ is (in my opinion) not a great language to start learning it, because a lot of it is hacked on top of C and implemented in arcane ways in order to maintain compatibility with C. The first language I learned was Java, and it was really helpful to have that as a background for when I learned C/C++. I’m only familiar with Javascript on a procedural programming level, so I’m not aware of its OO functionality or how well that will translate to C++, but hopefully it works out.

Good luck!

Yeah, I knew someone was going to say that. Usually it’s more likely that Python is installed than jq - especially on servers. But yes, that would definitely work too.

I use json.tool a lot to format JSON directly in vim. Simply highlight the text you want to format and run :!python3 -m json.tool. There are probably plugins to do this too, but doing it this way is probably the simplest, unless vim has a built-in for it.

Agreed overall, you will still be competent switching from one language to another, but intricacies and nuance matter a lot here. You may have enough knowledge to solve problems, but will you have enough knowledge to avoid creating new ones too? Like performance issues, or memory leaks, or other unwanted behavior? C++ is a great example here: someone that’s smart but inexperienced might just be dangerous enough to start writing classes with dumb pointers without overriding the copy constructors, and this is just a recipe for disaster.

I think it would take more than a few months to develop the kinds of experience that you need to be aware of these issues and avoid them. And while C++ is a very easy example to point out here, pretty much all languages have their share of footguns to be aware of, and it just takes time to learn them. A “deep knowledge” of a language is not just about being faster and more productive; it’s also about not creating more issues than the ones your solving.

This one might be a bit controversial, but has rung true in my general experience. Probably a lot of exceptions to these rules, but here goes:

You don’t really know a programming language until you understand a fair amount of the standard library and how packages/modules/dependencies work. Syntax is pretty easy, and any mainstream language will work just fine for solving basic leet-code style problems. But when you really spend a lot of time working with a language, you’re going to spend more time learning about common libraries and how to manage dependencies. If you’re working with a language like C++ or Java, this could also include build systems and how to use them.

Another precursor to being able to say that you know a language is that you should also be familiar with best practices (ie. how to name modules, how to write documentation, etc.) and common pitfalls (undefined behavior, etc.). This is one of the hardest parts about learning a new language in my opinion, because the language may not necessarily enforce these things, but doing them the wrong way can make your life very difficult.

the only annoyances are that to use the slash you need to use shift

Oof, that sounds really annoying. I can’t possibly imagine how I would use the terminal that way

But Swiss, that’s the stuff of nightmares!

Ha, that sounds funny (in a morbid kind of way…). What’s so bad about it?

There are terrible people everywhere. California and New York have 10s of millions of residents - there are bound to be some that are shitstains. The problem is that money = power and when it’s possible for one individual to have too much money, it inevitably means that terrible people will be able to amass this kind of power.

This is why wealth (in)equality is important - it’s what determines how much powerful individuals are able to become. If it’s too easy for a single person to amass too much power, inevitably, the wrong person will be able to gain it.

Møøse licks can be nasty, you know…

I think this is a misrepresentation. What more can Linux really do to get companies like this on board? It already has pretty much all anyone would need to support the platform: GUI toolkits, graphics drivers, etc. As far as I can see, Linux provides all the same functionality that other platforms do to support this, and considering that plenty of other companies support Linux just fine (Zoom, Steam, WPS office, etc.), in my opinion, it’s unfair to point fingers and say Linux is bad because other actors pointedly ignore it.

Off-topic, but I’m curious why you would put Nim in that list. While I absolutely love the language, I’ve never heard of anyone using it for anything serious, especially compared to Rust or even Zig. I’d even be surprised if it has more mindshare than D.

(An absolute shame by the way. Nim looks like an absolutely fantastic language.)

The net worth of tech giants also needs a severe correction.

Not just tech giants of course, pretty much all large >billion dollar companies need it too. But tech is a great place to start.