Slow Horses contains absolutely none of the complexity of Le Carre. They're in the same genre, but are not comparable.

The series you really want is The Night Manager.

Obviously, this assumes you've seen the BBC Tinker Tailor with Alec Guinness, the canonical Smiley.

It also stars an actor who played George Smiley in another film.

It's not! In NZ at least. 57% of our electricity is hydro.

Perhaps the author made it for themselves and not you...

Well it’d still be good to know why the author made it. Is it a toy language to learn about how to build a vm-interpreted language? Is it because the author can’t stand Python indentation. Or maybe there is a reason that clearly makes this interesting to use in the real world.

Because from the readme, it doesn’t look like this language brings anything to the table compared to Python/Node.

This is posted by the author himself, I find it pretty rude to let people figure out the point of their own project when promoting it.

“promoting” is a bit of an assumption. God bless Hacker News.

Is it? Irrespective of what I think of the post, I can't see any context in which posting it to a large forum full of strangers wouldn't count as 'promoting it'.

The most annoying thing when learning to program is that experienced programmers take your bullet points for granted -- and don't explain them well / don't explain them at all. But grokking those bullet points has a significant material impact on your ability to pick up the actual language itself later on.

The same is true when you're experienced -- programmers often say that programming is easy, which is because _syntax_ is often easy. It's the mechanics of how everything fits together that is difficult, and is often overlooked as a concept.

This was the point of the question :) To see what questions we need to ask if we're designing a software development environment in 2021. It may well be true that the current paradigm is sufficient: I was just curious what else came up.

Why wouldn't this have much value to pharma? Is it because its application is actually really limited in scope?

there are research groups this would be useful for but structures are not on the critical path to drug discovery or approval.

Out of (probably overoptimistic :) ) curiosity, what do you see are the critical paths?

I've been doing protein pharma research and the structure is only a first step, then years of figuring out the kinematics and dynamics of the protein, figuring out how it works, how all the natural ligands bind and affect the kinematics.. and only after all that you might conceivably start to engineer drug compounds (unless you bootstrap by a natural ligand to tweak "randomly", but then again, that's how pharma development traditionally works).

Still, even if structure determination is not on the "critical path", it IS a big barrier that has (started) to fall now.

Initial molecule generation and FDA approval.

Interesting! Could you explain? What C features doesn't C++ have?

- C has its own syntax for generics

- C has broader support for designated initializers

- C allows implicitly casting void* to any other pointer type

- C has fewer keywords, e.g. you can use "friend" or "class" as identifier

- ...

Despite all this, it's true enough that one can easily write C code that also compiles as C++.

- C has its own syntax for generics

C has generics?

Nothing like C++ or Rust generics. C has _Generic (type-switch macro): https://en.cppreference.com/w/c/language/generic

Go into pointer qualifiers and const with _Generic and you'll see that it's a mess to do anything serious with it. But it's handy for type-generic math (tgmath.h style) and that's seems to be about it.

Try half that salary for jobs in Australia and you might have more luck.

I've been thinking for a while that a (sort of) mix of the two would be worthwhile.

1. Personal knowledge bases seem to be high friction (have to manually add information and requires consistency).

2. Google is leaky, you search for something, open a bunch of tabs, and then probably just close them all. What happens when you need that info again?

I was thinking that a dashboard built on top of Google search would be helpful. Something that keeps a note of what content is related to the search I made, and keeps a record / makes it easy to retrieve again later.

(Yes I know the manual effort involved in documenting what you learn is beneficial).

> I've been thinking for a while that a (sort of) mix of the two would be worthwhile.

Perhaps, that is a better way to go about it but that just becomes a glorified notes app.

fuck this was funny