They're back!
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But my sandworms will die!
The spicy memes must flow!
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Hell yeah, welcome back!
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Not being able to participate anywhere on Lemmy merely because my home instance was down didn't feed very federated
Is there anything I can do to guard against that issue in the future? Is there a way to mirror an account between two instances or something?
Anyway, big props to the slrpnk admins for getting the instance back online quicker than expected. Your hard work is definitely not unappreciated or unnoticed.
I have alts. No automatic sync, but you can list your alts in your profile like I do.
On mobile make sure to use a client which makes it easy to switch between accounts (I use Thunder, which additionally shows server status in the account switcher!)
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Yaaaaay, welcome back y'all!
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You guys are the best. Thanks for the warm welcome back.
This post was actually how I learned slrpnk.net was back online.
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We're elated to be back in business. Brace yourself, my shitposting itch has gone unabated for a while now.
back to the meme mines with you
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And they want to migrate to piefed? Does it have better performance than Lemmy? That would be hilarious if python were faster than rust.
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Great news!
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And they want to migrate to piefed? Does it have better performance than Lemmy? That would be hilarious if python were faster than rust.
Tbh, the vast majority of performance issues don't come from the language but from the application itself.
While python is clearly slower than rust when it comes to pure native performance when doing exactly the same things exactly the same way and only within the language itself, the same isn't necessarily true in the bigger picture.
- Python uses C modules under the hood. A lot of the functions you call actually utilize C with C performance.
- Lower level languages allow the programmer to fail harder. While perfect low-level language code usually runs faster than perfect high-level language, the same cannot be necessarily said for bad or average code. For example, it's really hard to make an actual memory leak in Python. It's super easy to do so in languages without built-in memory management. The same applies in many other cases too. Python just gives you a lot of already-done tools that you only have to use, while other languages allow you to build the tools from scratch, which is easy to mess up.
- Most performance is lost due to using wrong algorithms or data structures. It's quite common when optimizing that you e.g. manage to eliminate a nested loop or something like that (e.g. loops hidden inside functions you call), and suddenly you improve performance by a factor of 1000. The same can't be done by switching languages, where even the most inefficient languages are only maybe 10x slower than the fastest languages.
So independent of the programming language, investing time in optimizing can improve the performance much more than using a faster language, and it's much easier to make perfectly optimized high-level language code than perfectly optimized low-level language code.
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Tbh, the vast majority of performance issues don't come from the language but from the application itself.
While python is clearly slower than rust when it comes to pure native performance when doing exactly the same things exactly the same way and only within the language itself, the same isn't necessarily true in the bigger picture.
- Python uses C modules under the hood. A lot of the functions you call actually utilize C with C performance.
- Lower level languages allow the programmer to fail harder. While perfect low-level language code usually runs faster than perfect high-level language, the same cannot be necessarily said for bad or average code. For example, it's really hard to make an actual memory leak in Python. It's super easy to do so in languages without built-in memory management. The same applies in many other cases too. Python just gives you a lot of already-done tools that you only have to use, while other languages allow you to build the tools from scratch, which is easy to mess up.
- Most performance is lost due to using wrong algorithms or data structures. It's quite common when optimizing that you e.g. manage to eliminate a nested loop or something like that (e.g. loops hidden inside functions you call), and suddenly you improve performance by a factor of 1000. The same can't be done by switching languages, where even the most inefficient languages are only maybe 10x slower than the fastest languages.
So independent of the programming language, investing time in optimizing can improve the performance much more than using a faster language, and it's much easier to make perfectly optimized high-level language code than perfectly optimized low-level language code.
Facts right here. I love Rust and my day job is Python. Neither is too slow for most of my use cases. Though one cool thing about Rust is the super low overhead. So well-written Rust, much like well-written C, is great for low-power devices. Still, the database is going to be memory, IOPS and maybe CPU hungry as it grows. You can optimize data structures, but you still need to read said data.
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And they want to migrate to piefed? Does it have better performance than Lemmy? That would be hilarious if python were faster than rust.
It is the medium term plan, yes (if feasible).
The user facing side of Piefed is more optimized for speed and low resource use, which fits well with our Solarpunk ethos, and on the backend side I expect it to be easier to maintain and the performance impact should be neglible as most of it is the Postgres database with Lemmy and likely Piefed as well.
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What is it meant to be?
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What is it meant to be?
I put the prompt in the alt-text
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I put the prompt in the alt-text
That's smart
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So happy to be home again ^^
Welcome back, and I agree!
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Tbh, the vast majority of performance issues don't come from the language but from the application itself.
While python is clearly slower than rust when it comes to pure native performance when doing exactly the same things exactly the same way and only within the language itself, the same isn't necessarily true in the bigger picture.
- Python uses C modules under the hood. A lot of the functions you call actually utilize C with C performance.
- Lower level languages allow the programmer to fail harder. While perfect low-level language code usually runs faster than perfect high-level language, the same cannot be necessarily said for bad or average code. For example, it's really hard to make an actual memory leak in Python. It's super easy to do so in languages without built-in memory management. The same applies in many other cases too. Python just gives you a lot of already-done tools that you only have to use, while other languages allow you to build the tools from scratch, which is easy to mess up.
- Most performance is lost due to using wrong algorithms or data structures. It's quite common when optimizing that you e.g. manage to eliminate a nested loop or something like that (e.g. loops hidden inside functions you call), and suddenly you improve performance by a factor of 1000. The same can't be done by switching languages, where even the most inefficient languages are only maybe 10x slower than the fastest languages.
So independent of the programming language, investing time in optimizing can improve the performance much more than using a faster language, and it's much easier to make perfectly optimized high-level language code than perfectly optimized low-level language code.
The main bottleneck is I/O anyway.
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.ca mentioned les goooooooo!
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But I was assured by entitled assholes that going down for a few days would be the absolute end of the community and it would never bounce back… I was assured it was extremely irresponsible bordering on criminal negligence for a hobby forum to not have at least three global points of presence each staffed with 24/7 on-call engineers.
