Business continuity plan testing day.

I’m sorry, who’s spreading hate and fear?

That’s it, I’m reporting you.

/s just in case

I wish this wasn’t so true.

LMAO we really have Lemmy cliques?

Plus you have plenty of time to tumble once or twice while your large codebase compiles.

Is there a language that anyone would say really does fare well for continued development or is it just that few people enjoy maintaining code? I’ve maintained some pretty old Go programs I wrote and didn’t mind it at all. I’ve inherited some brand new ones and wanted to rage quit immediately. I’ve also hated my own code too, so it’s not just whether or not I wrote it.

I have found maintainability is vastly more about the abstractions and architecture (modules and cohesive design etc) chosen than it is about the language.

In this economy I’m going to settle for a used threeskin in the next year or two.

The real primary benefit of storing your relationships in a separate place is that it becomes a point of entry for scans or alterations instead of scanning all entries of one of the larger entity types. For example, “how many users have favorited movie X” is a query on one smaller table (and likely much better optimized on modern processor architectures) vs across all favorites of all users. And “movie x2 is deleted so let’s remove all references to it” is again a single table to alter.

Another benefit regardless of language is normalization. You can keep your entities distinct, and can operate on only one of either. This matters a lot more the more relationships you have between instances of both entities. You could get away with your json array containing IDs of movies rather than storing the joins separately, but that still loses for efficiency when compared to a third relationship table.

The biggest win for design is normalization. Store entities separately and updates or scans will require significantly less rewriting. And there are degrees of it, each with benefits and trade-offs.

The other related advantage is being able to update data about a given B once, instead of everywhere it occurs as a child in A.

Judging by the stars I’m pretty sure it was night time.

In fairness, the mass surveillance is just more evenly distributed when civilian dashcams are proliferated.

I’m just imagining someone in a ghillie suit covering themselves in bird seed for an hour just to pop up at totality and hold down the shutter button while whispering a prayer.

Can we joke about log4shell? Maybe heartbleed?

Free money has dried up, so competition is drying up a bit too. And without free money, the big guys are feeling some squeeze and now want to extract the rent they always planned to eventually extract.

I watched them mindlessly for a while, starting recently. But then the algorithm just started showing me like the same 15 videos and nothing else. One or two new ones here and there, but it’s definitely fully lost any interest I had.

Can this power be learned?

Yeah, the image (not mine, but the best I found quickly) kinda shows a rebase+merge as the third image. As the other commenter mentioned, the new commit in the second image is the merge commit that would include any conflict resolutions.

Merge takes two commits and smooshes them together at their current state, and may require one commit to reconcile changes. Rebase takes a whole branch and moves it, as if you started working on it from a more recent base commit, and will ask you to reconcile changes as it replays history.

This is floating point. We also need to know what happens when you escape with -0.