Ok, I’ve done some double checking: The Bantu expansion is approximately what I thought it was. I believe the language group I was thinking about that survived the Bantu expansion was the Khoisan.

My (very coarse) knowledge of this comes from a mixture of reading Jared Diamond (Guns, Germs and Steel) and from following it up with some Wikipedia. In short: The genetic makeup in a lot of the world is relatively dominated by the groups that were the first to adopt agriculture in their respective regions. Before the Bantu expansion, phenotypes south of Sahara were more varied, just like the phenotypes in the Americas were more varied before the corresponding “European expansion”, or the equivalent expansion that happened in South-East Asia (I don’t remember which society stood behind that one).

According to Diamond, we can trace a lot of (most?) surviving human phenotypes and languages back to relatively few societies, which after adopting agriculture, more or less wiped out / displaced neighbouring cultures due to increased resistance to a lot of infectious diseases and massively increased food production / need for land. This mostly happened less than 10 000 years ago, i.e. far too recently for natural selection to have a major impact on things like skin colour, hair type, height, facial features, etc. afterwards.

So: While major trends in phenotypes are of course a result of natural selection / evolutionary pressure in specific regions (resistance to skin cancer / sunburn vs. vitamin D production, or cooling down more efficiently with a wider nose vs. retaining heat with a slimmer one, or having an eye-shape that lets in more light vs. provides more shade), a lot of what we see today is simply a result of what phenotype the first group a given region that adopted agriculture had. This means that looking at the dominant phenotype in a region today will not necessarily give a good impression of what phenotype that is “optimally designed” to survive in the conditions of that region.

I seem to remember that the majority traits south of Sahara (black/very dark skin, and curly hair) can be traced back to something called the “great Bantu expansion”, which was essentially the result of a group of people with these traits developing agriculture and wiping out most other peoples south of Sahara, much like the Europeans did to the Americas.

Some cultures south of Sahara did survive, which can be seen both genetically, and in some languages that are completely from other languages in the area (I believe the family of languages with “clicking” sounds is an example).

I’m on my phone now, but I’ll have a double check and come back.

Well if you need something to work with Fortran…

The whitespace doesn’t bother me at all, but holy hell! Any time I’m trying to understand a Python program/library that’s anything above a couple thousand lines of code, I instantly feel a burning hate for dynamic typing.

I love Python for scripting- in large part because of dynamic typing. IMO it’s just not a language made for building large infrastructures.

Sorry, but I honestly don’t get it. I I were to point out the crown jewel of open source, it’s gcc. gcc is the backbone and survival condition for so much modern industry that it’s not even remotely funny.

Take away gcc, and the world will likely burn for a substantial amount of time until people start making in-house or proprietary alternatives.

Don’t do that in Norway either - just bad luck if the holidays happen to land on a weekend. On the other hand, we have five weeks of paid vacation, and holidays are not counted into those, I’m not sure how that’s done in other countries?

I feel like it has something to do with the fact that there’s less content, so when you post something, it’s actually going to be seen by people.

I didn’t post or comment anything the last couple years on Reddit, largely because it increasingly felt like shouting into the void.

I am/was in the same boat as you: For a long time, I just didn’t care that I was giving away a bunch of information in return for convenience, and didn’t get why people cared so much.

I don’t really know what triggered it, but at some point I became painfully aware that the only goal these companies have is to squeeze every possible penny out of selling me. I started noticing that the stuff they ask you to confirm is 95% stuff they want because they can sell it, or use it to get you hooked to their service, and 5% (at best) stuff they need to make the service good for you.

This triggered a change in my perspective: Now it pretty much makes me sick to my stomach to think about all the companies that are drooling over me, trying to make a buck by getting me to click something I’m not actually interested in, or don’t actually need.

These people have a vested interest in manipulating me, and by giving them my data, I’m giving them the tools to do it. I don’t want to be manipulated or sold as a product: That’s what made me start caring about protecting my data.

This will sound dumb, but I’m saying it sincerely.

I’ve had similar issues (without getting into details), but what worked for me was getting outside a couple times a week. By that I mean bringing a tent or hammock + tarp and sleeping outside a couple nights a week on workdays.

To be specific: I sleep outside Monday-Tuesday and Wednesday-Thursday. On those days I also make my dinner at my campsite. What I’ve found is that my brain goes into a much more “primal” state of “monke outside in cold, monke get shit done”, and that it propagates into my day and week.

The barrier to this is of course actually going outside, but I’ve been able to get to a place where I have a “deal with myself” about those two nights a week. I always have my pack ready, so it’s just about grabbing it and heading out- I think that’s key.

I’m not saying this is a solution for everyone, but it’s done wonders for me. As of now, I get restless and feel bad if I’m in a situation where I can’t get outside at least once a week. It brings me a peace of mind and will to get stuff done that nothing else can.

I’ve never had an issue with this before, and as of now, my filter is catching most of these mails, so in that sense it’s not too bad. Unless the topic of the phishing attempts suddenly changes completely, in which case I’ll have to start building the filter again…

Anyway: The scam they’re running is relatively specific (a specific banking-thing that pretty much everyone in my country uses, written in not-English, probably LLM generated). Do you know if there’s any way I could alert my email-provider about this? I can imagine it’s being sent to quite a few people, and should be relatively easy for someone higher up the chain, with more sophisticated tools, to filter out.

Since you chose to point it out: My reason is that I regularly need to be able to log into things on a non-personal machine, sometimes without access to my phone. So no, a password manager for all my accounts is out of the picture. I either write stuff down, remember it, or - sometimes - forget it and need to reset my password.

Thanks! I’ll definitely look into that, though the only issue I can imagine is keeping track of which email that goes to which service (I’m one of those kinds of people that uses “Forgot my password” effectively as a password manager, don’t hate me for it, I have reasons).

Thanks! There was nothing there, so it may be from an older breach like you suggested :/

That’s what major versions are for - breaking changes. Regardless, you should probably be able to fix this with some regex hackery. Something along the lines of

new_file_content = re.sub(r'(?<=\bprint)(\s+)(?!\()', '(', old_file_content)
new_file_content = re.sub(r'(print\(.*?)(\n|$)', r'\1)', new_file_content)

should do the trick.

For someone starting out, I would say that a major advantage of Python over any compiled language is that you can just create a file and start writing/running code. With C++ (which I’m also a heavy user of) you need to get over the hurdle of setting up a build system, which is simple enough when you know it, but can quickly be a high bar for an absolute beginner. That’s before you start looking at things like including/linking other libraries, which in Python is done with a simple import, but where you have to set up your build system properly to get things working in C++.

Honestly, I’m still kind of confused that the beginner course at my old university still insists on giving out a pre-written makefile and vscode config files for everyone instead of spending the first week just showing people how to actually write and compile hello world using cmake. I remember my major hurdle when leaving that course was that I knew how to write basic C++, I just had no idea how to compile and link it when I could no longer use the makefile that we were explicitly told to never touch…

What does that have to do with non-Euclidean geometry?

Yes, it’s a field. Specifically, a field containing human-readable information about what is going on in adjacent fields, much like a comment. I see no issue with putting such information in a json file.

As for “you don’t comment by putting information in variables”: In Python, your objects have the __doc__ attribute, which is specifically used for this purpose.

My test suite takes quite a bit of time, not because the code base is huge, but because it consists of a variety of mathematical models that should work under a range of conditions.

This makes it very quick to write a test that’s basically “check that every pair of models gives the same output for the same conditions” or “check that re-ordering the inputs in a certain way does not change the output”.

If you have 10 models, with three inputs that can be ordered 6 ways, you now suddenly have 60 tests that take maybe 2-3 sec each.

Scaling up: It becomes very easy to write automated testing for a lot of stuff, so even if each individual test is relatively quick, they suddenly take 10-15 min to run total.

The test suite now is ≈2000 unit/integration tests, and I have experienced uncovering an obscure bug because a single one of them failed.

This is a very “yes but still no” thing in my experience. Typically, I find that if I write “naive” C++ code, where I make no effort to optimise anything, I’ll outperform python code that I’ve spent time optimising by a factor of 10-30 (given that the code is reasonably complex, this obviously isn’t true for a simple matrix-multiplication where you can use numpy). If I spend some time on optimisation, I’ll typically be outperforming python by a factor of 50+.

In the end, I’ve found it’s mostly about what kind of data structures you’re working with, and how you’re passing them around. If you’re primarily working with arrays of some sort and doing simple math with them, using some numpy and scipy magic can get you speeds that will beat naive C++ code. On the other hand, when you have custom data structures that you want to avoid unnecessarily copying, just rewriting the exact same code in C++ and passing things by reference can give you massive speedups.

When I choose C++ over python, it’s not only because of speed. It’s also because I want a more explicitly typed language (which is easier to maintain), overloaded functions, and to actually know the memory layout of what I’m working with to some degree.