It’s like if there was a library called QuickSort which also included a SAT solver and I then wrote an article about how you can solve SAT-equivalent problems with quicksort (“in the programmer sense, which obviously means a SAT solver”)

The distinction matters because regex absolutely can't match HTML, and because regex, unlike PCRE expressions, have guaranteed O(1) space and O(n) time complexity when matching a string of length n. When you use PCRE features for string matching, that may degrade to exponential time which makes it useless. For example, you can do denial of service PCRE attacks, but not denial of service regex attacks (unless you can query with some megabyte-large regex).

Best of luck to you, and get well. I’m glad it didn’t get even worse before it was treated.

Although I haven’t noticed a spike the last 6 months, just a slowly increasing realization that C isn’t fit for humans and should go the way of asbest: Don’t use it for anything new, and remove it where it already exists, unless doing so would be too expensive or disruptive.

In my experience you really gotta work with the tools the language gives you. Julia gives you Revise, so it’s a bit of a handicap not using it. Maybe analogous to writing Rust without an LSP.

I get that leaning on the LSP can become a habit, and also that the Julia LSP is quite poor, but I find it wild that rapid iteration for you is faster in Rust. I write Rust as well and can’t imagine how that would be the case.

It then gives you a bunch of new problems. First and foremost that you now work in a niche language with fewer packages and fewer people who can maintain the code. Then you get the huge JIT latency. And deployment issues. And lack of static tooling which Rust and Python have.

For me, as a research software engineer writing performance sensitive code, those tradeoffs are worth it. For most people, it probably isn’t. But if you’re the kind of person who cares about the Python optimization ladder, you should look into Julia. It’s how I got hooked.

China is far more serious than the EU about the green transition. Despite being poorer than the poorest EU country they are dominating renewable deployment.

I think that attitude is poorly informed whataboutism.

My own take is that Julia didn’t since the two language problem as much as was defeated by it.

Julia didn’t attract the high-level Python data science crowd because of Julia’s latency issue, lack of package ecosystem, and the inconveniences that a high performance compiled language incurs, such as having parametric containers.

The research software engineer crowds didn’t buy in because Julia has no interfaces or automatically checkable behavior, poor static tooling, imprecise semantics which is hard to build abstraction on, and a complex performance model that makes it hard to ensure speed, and is hard to deploy.

So, where they tried to make a language that can span the gap, they succeeded in making a language that works for neither, and which no-one wants.

I like the language. But after having used it for eight years, I find it increasingly hard to argue against the point that it’s better to choose Rust for software engineering and Python for scripting.

Edit: I should say: I used it for eight years because it IS fine for my specific niche: High performance research software engineering. Where I care neither about the convenience of Python, nor need to write truly robust and maintainable code. Where my choice of language was personal and I didn’t need to convince a team of coworkers.