However, before that, you need a lot of code to clean the data and raw data does not fit well into a structured RDBMS. Here you choose to either map your raw data into row view or a table view. You're now left with the choice of either inventing your own domain object (row view) or use a dataframe (table view).

For example, in Steam, it costs $100 to release a game. You may extend your game with what's called a DLC and that costs $0 to release. If I were to build shovelware with especially with AI-generated content, I'd more keen to make a single game with a bunch of DLC.

For game development, integration of AI into engines is another barrier. There aren't that many choices of engines that gives AI an interface to work with. The obvious interface is games that can be entirely build with code (e.g., pygame; even Godot is a big stretch)

Much prefer not thinking about venvs.

However, the focus on autocorrelation is not very illuminating. We can explain the behaviors found quite easily:

- If everyone's self-assessment score are (uniformally) random guesses, then the average self-assessment score for any quantile is 50%. Then of course those of lower quantile (less skilled) are overestimating.

- If self-assessment score vs actual score are dependent proportionally, then the average of each quantile is always at least it's quantile value. This is the D-K effect, which is weaker as the correlation grows.

-The opposite is true for disproportional relation.

So, the D-K plot is extremely sensitive to correlations and can easily over-exaggerate the weakest of correlations.

Why would you want to use C-like arrays in Python anyways?

Modern way of building a package is to use a build frontend. Most notably is the PyPA's build package.

    python -m build .

https://learn.scientific-python.org/development/guides/packa...

As a TLDR, you have many options 3rd party build tool (aka build backends). Each build tool have different *static* ways to specify compile options that is native to the language or generic (e.g., CMakeList,s Cargo.toml, 3rd party YAML. When it comes to dynamically specifying your extensions, setuptools is still the only option.

Following this standard, a tutorial may contain a simpler or more contrived example; it may contain things you'd never do in production.

It should be to learn who they are and what else the website provides. You're not there to read it's entire homepage. You're there to navigate.

The pages that need to be dense, like the standards document, are.

Single tally memory is useful on small screens. I just wish they’d display the stored value somewhere.