magic_lobster_party

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Joined 1 year ago
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Cake day: July 1st, 2023

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  • magic_lobster_party@kbin.social
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    toToday I Learned@lemmy.world...
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    4 months ago

    As you said, the difference is in the ecosystem of libraries. This is where Java has the edge. It has a more mature ecosystem when it comes to web server backends. This includes the number of frameworks, programmers and information sources.

    Unless Rust clearly solves common problems people currently have with Java backends, Java will remain the dominant alternative. I believe this is unlikely, because Rust is mainly designed to overcome common memory problems people have with low level C systems without the overhead of garbage collectors.


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    4 months ago

    It’s more that you can avoid many mistakes by programming defensively and having good discipline. For example, you can avoid many memory allocation if you follow RAII and use smart pointers.

    Null references can be avoided by avoiding using null (and prefer using optional where it makes sense).





  • The good thing about Python is that it’s widely used. Easier to find people who can contribute in Python than Rust, which Lemmy is using.

    Downside is that Python isn’t ideal for large scale systems. Other languages like Java is better at protecting the programmer against common pitfalls that come when building larger applications. Python is more ideal for smaller scripts.








  • magic_lobster_party@kbin.social
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    toAsklemmy@lemmy.mlHow are you?
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    5 months ago

    Not too bad, but could be better.

    A funny story about my not so great love life: just matched with a girl on Tinder which I managed to have engaging text discussions with and it felt quite genuine. This is rare for me, so I was happy about it.

    Well, in the end it became obvious to me it was just a pig butchering romance scam when she started to talk about how she can help me invest in cryptocurrency.

    I guess I’m going to be a failure in love life for a bit longer lol.





  • Often I use Python for exploratory purposes. Like, I got a bunch of data, and I want to know if a particular algorithm might work or not. I implement the algorithm, but realize the results don’t look good enough. So I tweak the algorithm, maybe even do major refactoring. Or maybe I realize my visualizations or metrics don’t capture what I need to see. Or maybe I must settle for some compromise?

    I iterate on this repeatedly until I find something I’m happy about (or until I give up). Sometimes I end up with something completely different from my initial idea.

    TDD won’t help me much here because the end result is unknown. For each iteration of this idea process I might even need to rewrite all the tests because none of them are valid anymore.