Show HN: Claude Artifacts" but creating real web apps
21 by antonoo | 9 comments on Hacker News. Hey Hacker News! Launching gptengineer.app into beta today. It's like Claude Artifacts, but: - you can edit the code in your fav IDE (two-way github sync) - installs npm packages - automatically picks up build and runtime errors and fixes them - very fast, built with rust The full stack capabilities are built on supabase (prefer to not have to handle auth + user data at this point so this is owned by the user) The seed for this project was an open source experiment, posted about that previously here: https://ift.tt/xo49QMI Would love feedback if you give it a try!
Why don't we have personalized search engines?
18 by enether | 20 comments on Hacker News. - Search as it is today sucks - Google is an ad-engine, not a search engine - SEO is gamed all the time The end result is a search result that isn't that valuable. Why isn't there a tool that allows me to: - search good content I've read - search curated (from other people I trust) content - search books and other paid material I have bought - search my notes (that are scattered throughout 5 apps) All in one?
Jakob Ingebrigtsen smashes the 3,000m world record before Armand Duplantis breaks his own pole vault world record at the Diamond League event in Silesia.
Show HN: Tree-sitter Integration for Swift
9 by daspoon | 1 comments on Hacker News. I have created a Swift package ( https://ift.tt/zIxydCY ) enabling tree-sitter parsers to be written in Swift; specifically, as an array of production rules which map symbol types to pairings of syntax expression and type constructor. A member macro derives a tree-sitter grammar and embeds the generated parser in its expansion. This project is a work in progress, and I will be grateful for any feedback. Thanks, Dave
Show HN: Denormalized – Embeddable Stream Processing in Rust and DataFusion
24 by ambrood | 4 comments on Hacker News. tl;dr we built an embeddable stream processing engine in Rust using apache DataFusion, check us out at https://ift.tt/0TyS8tj Hey HN, We’d like to showcase a very early version of our embeddable stream processing engine called Denormalized. The rise of DuckDB has abundantly made it clear that even for many workloads of Terabyte scale, a single node system outshines the distributed query engines of previous generation such as Spark, Snowflake etc in terms of both performance and cost. Now a lot of workloads DuckDB is used for were normally considered to be “big data” in the previous generation, but no more. In the context of streaming especially, this problem is more acute. A streaming system is designed to incrementally process large amounts of data over a period of time. Even on the upper end of scale, productionized use-cases of stream processing are rarely performing compute on more than tens of gigabytes of data at a given time. Even so, the standard stream processing solutions such as Flink involve spinning up a distributed JVM cluster to even compute against the simplest of event streams. To that end, we’re building Denormalized designed to be embeddable in your applications and scale up to hundreds of thousands of events per second with a Flink-like dataflow API. While we currently only support Rust, we have plans for Python and Typescript bindings soon. We’re built atop DataFusion and the Arrow ecosystems and currently support streaming joins as well as windowed aggregations on Kafka topics. Please check out out repo at: https://ift.tt/0TyS8tj We’d love to hear your feedback.
Ask HN: How different is AWS/GCP/Azure in everyday work
23 by michal_kluczek | 17 comments on Hacker News. I've almost exclusively been working with GCP for years, with very few occasions when I've created some resources in AWS (I'm managing infra using terraform). When looking a job now, it's very common that I'm rejected before TI because I wasn't working with AWS. Is it really so fundamentally different from GCP or any other cloud provider for that matter? I have a wild feeling that 80-90% of the products all cloud providers offer are same toys but with different names and integrations mechanisms. There are surely some quirks that are exclusive for a specific cloud provider, but is it really that many to stifle your performance?