For example, when working with arrays of data it certainly is easier to think and write “avg a+b” to add two arrays together and then take the average.

In a non-array programming language you would probably first need to do some bounds checking, then a big for loop, a temporary variable to hold the sum and the count as you loop over the two arrays, etc.

Probably the difference between like 6ish lines of code in some language like C versus the 6 characters above in Q.

But every language has features that help you reason about certain types of problems better. Functional languages with algebraic data types and pattern matching (think OCaml or F#) are nicer than switch statements or big if-else-if statements. Languages with built-in syntactic sugar like async/await are better at dealing with concurrency, etc.

Capitalism is not perfect, but at least to me this is more of a moral issue than an economic one.

I think your CO2 point is a great example, why would a Communist or Socialist economic system be inherently more eco-friendly than a Capitalist system? You now have a system where there is a government willing to "plan" or "intervene" in certain aspects of the economy, but unless the government actually cares about pollution nothing will happen. You could even theoretically have a centrally-planned economy that WANTS to increase emissions.

The largest polluter in the world is a Communist country, and in the last 30 years their CO2 emissions have sextupled, while the US's emissions per year have remained flat.

Morality != Economics

I think you touch on something really interesting which is the kink in the kdb+ learning curve when you go from really simple functions,tables, etc. to actually building a performant kdb architecture.

- charting

- machine learning/statsmodels

- html processing/webscrapes

Because for example you can just open a Jupyter Notebook and do:

  import pykx as kx
  df = kx.q(“select from foo where bar”)
  plt.plot(df[“x”], df[“y”])

It’s legitimately 2 million enslaved Muslims imprisoned, working for $0.

https://selectcommitteeontheccp.house.gov/sites/evo-subsites...

For example, my work virtual machine on Azure can't ever use it.

One potential option but definitely a bit more work would be, once you have all the warc files downloaded, you can open them all in python using the warctools module and maybe beautifulsoup and potentially parse/extract all of the data embedded in the WARC archives into your own "fresh" HTML webserver.

https://github.com/internetarchive/warctools