Piefed contributor and part of the piefed.social admin team.

  • 22 Posts
  • 62 Comments
Joined 1 year ago
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Cake day: November 20th, 2024

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  • Follow-up question: I am trying to get a feel for the “international hit” rule and how to apply it in this case. Anime is already a bit of a niche, but it can certainly break out into the mainstream, and I don’t want to contravene the spirit of this event by just choosing something that already hit it big so to speak.

    My initial thought for an easy way to gauge this for our community is that videos over a view threshold should be excluded. An arbitrary value might be something like 10M or so. Looking over the award nominees from 2025 in the community for musical piece, that would exclude 3 of the 6 nominees.

    Does that seem reasonable?





  • My experience is in Lightroom, not Darktable, but LUTs just take an RGB value at each pixel and map it to a different RGB value. The LUT (look up table) is just a big table containing these mappings. They are most commonly used near the end of the development pipeline to do color grading. It’s a common way to do something like emulate the color response of a specific type of film, even if you shot digitally.

    So, typically I would do my developing (lens profile, crop, exposure, etc.) first, then apply a LUT. After the LUT, then I would tweak the color sliders if there are any I still want to adjust. The color is usually the last step of the process for me.

    All that being said, these days I don’t really use LUTs any longer. I am mostly doing product photography using a flash in a controlled studio environment. So, I pretty much have some develop presets all dialed in.





  • @blaze@piefed.zip has been asking for this feature for ages and @Skavau@piefed.social made an issue for it on the codeberg already. The reason this isn’t in the api yet is because it isn’t anywhere in piefed yet. AFAIK, the read/unread status of comments isn’t currently tracked anywhere within piefed. Additionally, for this feature, I don’t believe we track the timestamp at which you do interact with a post…so doing something like calculating the number of new comments that have occurred since you last opened that post isn’t possible…yet.

    I don’t have a great idea of how to do this in a db-efficient way. Keeping track of when every user opens each post sounds like db-query hell. However, there might be clever caching tricks to make it a bit less computationally intense. @rimu@piefed.social would likely have a better idea of how to do this.














  • I run a personal lemmy instance and two personal piefed instances, so I was just doing some comparisons. My instances are mainly used for development and testing, so they are only subscribed to a handful of communities and just have one active user.

    You are correct that when it comes to performance, like snappiness and responsiveness, the database is probably going to be the bottleneck. Unless you are scaling up to a huge degree, I would be surprised to see meaningful differences in the number of requests that could be handled due to language differences between rust and python. Yes, python is an interpreted language, but most of the libraries you are using are basically calling other system libraries written in a language like C, and the program can execute way faster than your database I/O can give it data to process anyway.

    Here is my usage summary. The lemmy instance has been running for about 1.5 years while the piefed instance has been running for just shy of a year now. I have only included the memory usage and disk since I don’t think either is really CPU hungry or bound in my use case.

    Software Memory consumption Disk Usage
    Lemmy ~1.5 GB ~800 MB
    Piefed ~1 GB ~200 MB