Show HN: PredicateKit – A type-safe replacement for NSPredicate for CoreData https://ift.tt/TSmg8B5

Show HN: PredicateKit – A type-safe replacement for NSPredicate for CoreData Hi, I really like CoreData. I think it's a great piece of software (I know this is a controversial opinion in some circles ;)). My only pet peeve with it has been the string-based querying API based on NSPredicate. It is a major source of bugs/crashes and doesn't really fit nicely in the modern strongly-typed world of Swift. I built PredicateKit as a lightweight replacement for NSPredicateKit (specifically for CoreData) that makes writing predicates as safe and pleasant as writing native Swift code. https://ift.tt/OIM7bcm April 5, 2024 at 05:03AM

Show HN: FizzBee – Formal methods in Python – Easiest Lang for everyday use https://ift.tt/qgusjCP

Show HN: FizzBee – Formal methods in Python – Easiest Lang for everyday use GitHub: https://ift.tt/hA16ex2 Traditionally, formal methods are used only for highly mission critical systems to validate the software will work as expected before it's built. Recently, every major cloud vendor like AWS, Azure, Mongo DB, confluent, elastic and so on use formal methods to validate their design like the replication algorithm or various protocols doesn't have a design bug. I used TLA+ for billing and usage based metering applications. However, the current formal methods solutions like TLA+, Alloy or P and so on are incredibly complex to learn and use, that even in these companies only a few actually use. Now, instead of using an unfamiliar complicated language, I built formal methods model checker that just uses Python. That way, any software engineer can quickly get started and use. I've also created an online playground so you can try it without having to install on your machine. In addition to model checking like TLA+/PlusCal, Alloy, etc, FizzBee also has performance and probabilistic model checking that be few other formal methods tool does. (PRISM for example, but it's language is even more complicated to use) Please let me know your feedback. Url: https://FizzBee.io Git: https://ift.tt/hA16ex2 https://fizzbee.io/ April 2, 2024 at 04:15PM

Show HN: Managed GitHub Actions Runners for AWS https://ift.tt/vBQtiN2

Show HN: Managed GitHub Actions Runners for AWS Hey HN! I'm Jacob, one of the founders of Depot ( https://depot.dev ), a build service for Docker images, and I'm excited to show what we’ve been working on for the past few months: run GitHub Actions jobs in AWS, orchestrated by Depot! Here's a video demo: https://www.youtube.com/watch?v=VX5Z-k1mGc8 , and here’s our blog post: https://ift.tt/Hmv2GFM . While GitHub Actions is one of the most prevalent CI providers, Actions is slow, for a few reasons: GitHub uses underpowered CPUs, network throughput for cache and the internet at large is capped at 1 Gbps, and total cache storage is limited to 10GB per repo. It is also rather expensive for runners with more than 2 CPUs, and larger runners frequently take a long time to start running jobs. Depot-managed runners solve this! Rather than your CI jobs running on GitHub's slow compute, Depot routes those same jobs to fast EC2 instances. And not only is this faster, it’s also 1/2 the cost of GitHub Actions! We do this by launching a dedicated instance for each job, registering that instance as a self-hosted Actions runner in your GitHub organization, then terminating the instance when the job is finished. Using AWS as the compute provider has a few advantages: - CPUs are typically 30%+ more performant than alternatives (the m7a instance type). - Each instance has high-throughput networking of up to 12.5 Gbps, hosted in us-east-1, so interacting with artifacts, cache, container registries, or the internet at large is quick. - Each instance has a public IPv4 address, so it does not share rate limits with anyone else. We integrated the runners with the distributed cache system (backed by S3 and Ceph) that we use for Docker build cache, so jobs automatically save / restore cache from this cache system, with speeds of up to 1 GB/s, and without the default 10 GB per repo limit. Building this was a fun challenge; some matrix workflows start 40+ jobs at once, then requiring 40 EC2 instances to launch at once. We’ve effectively gotten very good at starting EC2 instances with a "warm pool" system which allows us to prepare many EC2 instances to run a job, stop them, then resize and start them when an actual job request arrives, to keep job queue times around 5 seconds. We're using a homegrown orchestration system, as alternatives like autoscaling groups or Kubernetes weren't fast or secure enough. There are three alternatives to our managed runners currently: 1. GitHub offers larger runners: these have more CPUs, but still have slow network and cache. Depot runners are also 1/2 the cost per minute of GitHub's runners. 2. You can self-host the Actions runner on your own compute: this requires ongoing maintenance, and it can be difficult to ensure that the runner image or container matches GitHub's. 3. There are other companies offering hosted GitHub Actions runners, though they frequently use cheaper compute hosting providers that are bottlenecked on network throughput or geography. Any feedback is very welcome! You can sign up at https://ift.tt/VZr48T0 for a free trial if you'd like to try it out on your own workflows. We aren't able to offer a trial without a signup gate, both because using it requires installing a GitHub app, and we're offering build compute, so we need some way to keep out the cryptominers :) April 4, 2024 at 08:02PM

Show HN: Logfmtxx – Header only C++23 structured logging library using logfmt https://ift.tt/YODNs4h

Show HN: Logfmtxx – Header only C++23 structured logging library using logfmt https://ift.tt/wuQCEb3 April 4, 2024 at 07:22AM

Show HN: AI generator for faceless TikTok videos https://ift.tt/DO4hX2U

Show HN: AI generator for faceless TikTok videos Hi there Several months ago I launched an app called LogoPicture AI. It's a simple app that generates picture in the style of your logo. Last week I sold this app. It was my first app ever which generated some revenue. But I really struggled with marketing. I tried SEO, TikTok, Twitter - many other things. And one thing I realized that in marketing you need to be super consistent to win. You need to create a video every day, a post, etc. But I am too lazy for this :)) So, this is how the idea of Cliplama was born. I wanted to automate my marketing. I wanted to create a tool what will do at least some marketing for me. A tool, that will create a popular social account for me and I will be able to funnel its traffic in my apps. So yeah, this is that Cliplama is about. It helps you to create faceless TikTok or even YouTube channel and just post there videos daily. That's it. Right now Cliplama is in beta, so there are some bugs for sure. Some features are also missing. But I felt like it's a time to launch it. Would love to hear your feedback. Thank you! https://cliplama.com/ April 3, 2024 at 09:50PM

Show HN: I just open sourced my document/website extractor for Vision-LLMs https://ift.tt/kZ9Q2rp

Show HN: I just open sourced my document/website extractor for Vision-LLMs Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it out and hopefully offer some feedback / criticism or contribute to the code yourself. and BTW, I'm not trying to throw shade at any of the services mentioned, I'm just giving my honest experience in case there are others out there who feel the same way and want something that works Cheers! https://ift.tt/ePlsfS4 April 3, 2024 at 12:10AM

Show HN: Apprise-API – All in one notification solution with API access point https://ift.tt/4hv7Py3

Show HN: Apprise-API – All in one notification solution with API access point https://ift.tt/bIL97QX April 3, 2024 at 12:29AM