The best Hacker News stories from Show from the past week
Latest posts:
Show HN: I built a site that finds the cheapest place to buy a book
Show HN: I built a site that finds the cheapest place to buy a book
Show HN: Lambda-8cc – An x86 C compiler written in untyped lambda calculus
Show HN: RankedVote – SurveyMonkey but focused on ranked-choice voting
RankedVote is a web app that allows you to run online contests and make decisions using ranked-choice voting (RCV). RCV is an electoral system used in Maine, Alaska, New York City and dozens of cities across the United States.<p>RankedVote’s goal is to build support for RCV by giving people an easy way to run contests and make decisions online.
Show HN: Sharing, command-line tool to share files with your phone
Sharing is a command-line tool to share directory and files with ios and android devices without an extra client app
Show HN: Async UI: A Rust UI Library Where Everything is a Future
Show HN: I finished v5 of a JVM framework I've spent spent half a decade making
Show HN: SigNoz – open-source alternative to DataDog, NewRelic
Show HN: SigNoz – open-source alternative to DataDog, NewRelic
Show HN: Stock Photos Using Stable Diffusion
Hi HN, this is an early version of what we’re imagining as a truly functional stock photo platform using Stable Diffusion.<p>We’re doing our best to hide the customization prompts on the back end so users are able to quickly search for pre-existing generated photos, or create new ones that would ideally work as well.<p>If we keep going with it, in future versions we’d like to add voting, better tags, and more varied prompts, or maybe whatever you recommend!
Show HN: Stock Photos Using Stable Diffusion
Hi HN, this is an early version of what we’re imagining as a truly functional stock photo platform using Stable Diffusion.<p>We’re doing our best to hide the customization prompts on the back end so users are able to quickly search for pre-existing generated photos, or create new ones that would ideally work as well.<p>If we keep going with it, in future versions we’d like to add voting, better tags, and more varied prompts, or maybe whatever you recommend!
Show HN: Stock Photos Using Stable Diffusion
Hi HN, this is an early version of what we’re imagining as a truly functional stock photo platform using Stable Diffusion.<p>We’re doing our best to hide the customization prompts on the back end so users are able to quickly search for pre-existing generated photos, or create new ones that would ideally work as well.<p>If we keep going with it, in future versions we’d like to add voting, better tags, and more varied prompts, or maybe whatever you recommend!
Show HN: uFuzzy.js – A tiny, efficient fuzzy search that doesn't suck
Hello HN!<p>I became frustrated with the unpredictible/poor match quality and opaqueness of "relevance scores" in existing fuzzy and fulltext search libs, so I tried something different and this is the result. The main selling point is the result quality / ordering, with best-in-class memory overhead and excellent performance being bonuses. The API is pretty stable at this point, but looking for feedback before committing to 1.0.<p>TL;DR<p>The test corpus is a 4MB json file with 162k words/phrases, so give it a second for initial download. You can also drag/drop your own text/json corpus into the UI to try it against your own dataset.<p>Live demo/compare with a few other libs (there are many more in the codebase, in various states of completion, WIP):<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy,fuzzysort,QuickScore,Fuse&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>In isolation for perf assessment:<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>To increase fuzziness and get broader results, try setting intraMax=1 (core) and enable outOfOrder (userland):<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy&outOfOrder&intraMax=1&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>Also play with the sortPreset selector to swap out the default Array.sort() for one in userland that prioritizes typehead-ness (the resultset remains identical).<p>Still TODO:<p><pre><code> - Example of stripping diacritics
- Example of using non-latin charsets
- Example of prefix-caching to improve typeahead perf even further
- Example of poor man's document search (matching multiple object properties)
</code></pre>
That's all, thanks!
Show HN: uFuzzy.js – A tiny, efficient fuzzy search that doesn't suck
Hello HN!<p>I became frustrated with the unpredictible/poor match quality and opaqueness of "relevance scores" in existing fuzzy and fulltext search libs, so I tried something different and this is the result. The main selling point is the result quality / ordering, with best-in-class memory overhead and excellent performance being bonuses. The API is pretty stable at this point, but looking for feedback before committing to 1.0.<p>TL;DR<p>The test corpus is a 4MB json file with 162k words/phrases, so give it a second for initial download. You can also drag/drop your own text/json corpus into the UI to try it against your own dataset.<p>Live demo/compare with a few other libs (there are many more in the codebase, in various states of completion, WIP):<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy,fuzzysort,QuickScore,Fuse&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>In isolation for perf assessment:<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>To increase fuzziness and get broader results, try setting intraMax=1 (core) and enable outOfOrder (userland):<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy&outOfOrder&intraMax=1&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>Also play with the sortPreset selector to swap out the default Array.sort() for one in userland that prioritizes typehead-ness (the resultset remains identical).<p>Still TODO:<p><pre><code> - Example of stripping diacritics
- Example of using non-latin charsets
- Example of prefix-caching to improve typeahead perf even further
- Example of poor man's document search (matching multiple object properties)
</code></pre>
That's all, thanks!
Show HN: uFuzzy.js – A tiny, efficient fuzzy search that doesn't suck
Hello HN!<p>I became frustrated with the unpredictible/poor match quality and opaqueness of "relevance scores" in existing fuzzy and fulltext search libs, so I tried something different and this is the result. The main selling point is the result quality / ordering, with best-in-class memory overhead and excellent performance being bonuses. The API is pretty stable at this point, but looking for feedback before committing to 1.0.<p>TL;DR<p>The test corpus is a 4MB json file with 162k words/phrases, so give it a second for initial download. You can also drag/drop your own text/json corpus into the UI to try it against your own dataset.<p>Live demo/compare with a few other libs (there are many more in the codebase, in various states of completion, WIP):<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy,fuzzysort,QuickScore,Fuse&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>In isolation for perf assessment:<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>To increase fuzziness and get broader results, try setting intraMax=1 (core) and enable outOfOrder (userland):<p><a href="https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uFuzzy&outOfOrder&intraMax=1&search=super ma" rel="nofollow">https://leeoniya.github.io/uFuzzy/demos/compare.html?libs=uF...</a><p>Also play with the sortPreset selector to swap out the default Array.sort() for one in userland that prioritizes typehead-ness (the resultset remains identical).<p>Still TODO:<p><pre><code> - Example of stripping diacritics
- Example of using non-latin charsets
- Example of prefix-caching to improve typeahead perf even further
- Example of poor man's document search (matching multiple object properties)
</code></pre>
That's all, thanks!
ButtFish – Transmit Morse Code of chess moves to your butt
ButtFish – Transmit Morse Code of chess moves to your butt
Show HN: Depot – fast, remote Docker container builds
Hey HN! We’re Kyle and Jacob and we are excited to show you Depot (<a href="https://depot.dev" rel="nofollow">https://depot.dev</a>) and get your feedback!
Depot is a hosted Docker container build service, providing fully managed remote builds from CI and from your terminal. We support both Intel and Arm builds natively.<p>As application and platform engineers, we have experienced the challenge of keeping Docker container build times fast. From optimizing and reoptimizing Dockerfiles, to implementing layer caching in CI, to running & maintaining custom runners for multi-platform images.<p>Still today, there are limitations with the available tools. CI runners are ephemeral, and saving and loading cache tarballs is slow. CI providers are resource constrained, with limited CPUs and disk space to dedicate to fast builds. And with the increasing popularity of Arm devices like M1, Graviton, etc, building multi-platform images requires slow emulation or self-hosted infrastructure.<p>We created Depot to directly address those limitations. Depot provides managed VMs running BuildKit, the backing build engine for Docker. Each VM includes 4 CPUs, 8GB of memory, and a persistent 50GB SSD cache disk. We launch both native Intel and native Arm machines, on Fly.io for Intel builds and AWS for Arm.<p>We have built a depot CLI that embeds the Docker buildx build library, implementing the same CLI flags, so developers can send their builds to Depot VMs just by replacing `docker buildx build` with `depot build`. We also have a depot/build-push-action GitHub Action that can be swapped for docker/build-push-action in CI.<p>The combination of native CPUs, fast networks, and persistent disks significantly lowers build time — we’ve seen speedups of 2-3x on optimized projects, and as much as a 12x speedup with some of our customers.<p>We believe that today we are the only hosted CI or build service offering the ability to natively build multi-platform Docker images (--platform linux/amd64,linux/arm64) without emulation.<p>We are still early though, and would love your feedback.<p>You can sign up without a credit card at <a href="https://depot.dev/sign-up" rel="nofollow">https://depot.dev/sign-up</a> to access a free project with thirty days of unlimited build minutes to try it out.
Show HN: Depot – fast, remote Docker container builds
Hey HN! We’re Kyle and Jacob and we are excited to show you Depot (<a href="https://depot.dev" rel="nofollow">https://depot.dev</a>) and get your feedback!
Depot is a hosted Docker container build service, providing fully managed remote builds from CI and from your terminal. We support both Intel and Arm builds natively.<p>As application and platform engineers, we have experienced the challenge of keeping Docker container build times fast. From optimizing and reoptimizing Dockerfiles, to implementing layer caching in CI, to running & maintaining custom runners for multi-platform images.<p>Still today, there are limitations with the available tools. CI runners are ephemeral, and saving and loading cache tarballs is slow. CI providers are resource constrained, with limited CPUs and disk space to dedicate to fast builds. And with the increasing popularity of Arm devices like M1, Graviton, etc, building multi-platform images requires slow emulation or self-hosted infrastructure.<p>We created Depot to directly address those limitations. Depot provides managed VMs running BuildKit, the backing build engine for Docker. Each VM includes 4 CPUs, 8GB of memory, and a persistent 50GB SSD cache disk. We launch both native Intel and native Arm machines, on Fly.io for Intel builds and AWS for Arm.<p>We have built a depot CLI that embeds the Docker buildx build library, implementing the same CLI flags, so developers can send their builds to Depot VMs just by replacing `docker buildx build` with `depot build`. We also have a depot/build-push-action GitHub Action that can be swapped for docker/build-push-action in CI.<p>The combination of native CPUs, fast networks, and persistent disks significantly lowers build time — we’ve seen speedups of 2-3x on optimized projects, and as much as a 12x speedup with some of our customers.<p>We believe that today we are the only hosted CI or build service offering the ability to natively build multi-platform Docker images (--platform linux/amd64,linux/arm64) without emulation.<p>We are still early though, and would love your feedback.<p>You can sign up without a credit card at <a href="https://depot.dev/sign-up" rel="nofollow">https://depot.dev/sign-up</a> to access a free project with thirty days of unlimited build minutes to try it out.
Show HN: Refurb – A tool for refurbishing and modernizing Python codebases