![](https://lemmy.stuart.fun/pictrs/image/910b6b99-09cf-4901-ba16-a9b3fff89e56.png)
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Believe it or not, straight to jail.
Just chilling
Believe it or not, straight to jail.
LMAO we really have Lemmy cliques?
Sandpaper remote, coming right up!
It’ll probably be stored in something like a TPM, whose primary purpose is to make intact extraction of the keys difficult or impossible. A few keys might become compromised but in this scenario (unlike DRM decryption) it’s easy to ignore those keys. There’s always the chance an exploit becomes available and is more widely used, though, in which case it would definitely be less valuable.
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.
Huuuge… Tracts of land.
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.
Understandable, have a nice day.
I ordered them through Lowes and they had all sorts of options for connectivity and power, including just old school chains. Looks like they’re Bali brand.
Haven’t watched the video yet, but I’m a huge fan of our plug-in z-wave smart blinds. Makes getting all that extra light way easier and automatable.
Piracy is just staying over at a friend’s house.
Right. Even if they wanted to change the behavior for everyone, this feature should have included another button that has the old behavior. More evidence that Google has long jumped the shark.
How very apt that Hollywood would be so skilled at projection.
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.
I mean, I’ve had this prepared professionally and it was exceptional and consistent. And I knew immediately I probably didn’t ever want to prepare it myself.
Or homeassistant. Or gitlab/github actions. So much yaml.
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I wish this wasn’t so true.