The best Hacker News stories from Show from the past day
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Show HN: Visual DB – Web front end for your database
If you have a cloud-hosted database, read on: Visual DB was designed for you.<p>Visual DB is the fastest way to create data entry forms for your database: Starting with an Excel spreadsheet, you can import your data into the database and create a great-looking form in under 10 minutes. Watch this video: <a href="https://youtu.be/6rVD5rmrjN8" rel="nofollow">https://youtu.be/6rVD5rmrjN8</a><p>Visual DB is a comprehensive SaaS frontend for your database. In addition to data entry forms, Visual DB also has a spreadsheet-like interface for inserting and updating data in your database. You can also build interactive reports using Visual DB. Finally, although not intended as a replacement for your database's admin tool, Visual DB can browse schema, create tables, set up relationships, and import and export data.<p>Visual DB began as a drag-and-drop form builder for databases. Forms created with Visual DB are practically indistinguishable from those hand-coded using React. You can add client-side validation, set available values (displayed in dropdowns), define default values, and even add logic to dynamically hide or disable fields—all without writing a single line of code! With Visual DB Forms, you’ll never have to write another CRUD app again.<p>If you have been using Excel to manage data and running into its limits because the volume of data has grown, Visual DB Sheets may be of interest to you. With its spreadsheet-like interface, Visual DB Sheets allows users to interact with data as they would in Excel, while securely storing that data in a robust relational database. Spreadsheet-database hybrids have been around for a while now, but we believe we have one of the best implementations, with features such as advanced grouping, support for foreign keys and lookup tables, query parameters, full-text as-you-type filtering, and so on.<p>The newest feature of Visual DB is interactive reporting. Traditional reporting tools offer limited interactivity. For example, while most reporting tools support time series charts, they do not allow users to zoom or pan along the time axis. In contrast, Visual DB supports this capability thanks to its innovative approach: it downloads the dataset to the client and processes and visualizes data directly in the browser. This allows it to handle user interactions without a server round trip. Visual DB has excellent support for query parameters, which allows you to bring only the subset of data that's of interest (up to 100K rows), to the client.<p>Visual DB supports PostgreSQL (including Neon), MySQL, SQL Server and Oracle. Give it a whirl, and we look forward to getting your feedback: <a href="https://visualdb.com" rel="nofollow">https://visualdb.com</a>
Show HN: YourNextStore – an open-source Shopify with Stripe as the back end
We’re building Your Next Store, a modern, ultra-fast, open-source commerce in Next.js with Stripe as the backend - no DB required.<p>Selling online is often more complex than it needs to be. Setting up a storefront with great performance can feel daunting and time-consuming. There are many plugins, libraries, etc - the choice can be overwhelming.<p>Plus, in e-commerce, the backend and frontend are often written in different languages (e.g., PHP, Python, or Ruby for the backend). This increases the complexity and makes code management more challenging, especially for teams.<p>After working in e-commerce for several years, Michał and I set out to build the fastest and most compelling storefront for small to medium-sized merchants. Fast e-commerce sites are crucial because slow pages hurt sales [1]. Unfortunately, performance issues are still very common. The beauty of Your Next Store is its simplicity. No additional tools and no databases - just Next.js and Stripe.<p>On the technical side, we use App Router, React Server Component, Partial Pre-Rendering, Optimistic Updates, and Streaming with Suspense to make the store faster and leaner so it feels almost like a static website.<p>In summary:<p>Modern & Popular Stack: Built with Next.js, React.js, and TypeScript, making development faster and hiring easier compared to platforms that use less common frameworks like Shopify’s Liquid.<p>No Database Needed: Stripe handles the backend, reducing the need for complex infrastructure and simplifying the setup process.<p>Open Source: Free and open (AGPL), with the option for a commercial license if needed.<p>This is just the beginning. We want to make YNS even better and easier to use and eventually provide a good, open-source alternative to Shopify.<p>Check our code at <a href="https://github.com/yournextstore/yournextstore">https://github.com/yournextstore/yournextstore</a><p>We’d love to hear your thoughts and feedback! What features would you like to see next?<p>[1]: <a href="https://www.deloitte.com/ie/en/services/consulting/research/milliseconds-make-millions.html" rel="nofollow">https://www.deloitte.com/ie/en/services/consulting/research/...</a>
Show HN: YourNextStore – an open-source Shopify with Stripe as the back end
We’re building Your Next Store, a modern, ultra-fast, open-source commerce in Next.js with Stripe as the backend - no DB required.<p>Selling online is often more complex than it needs to be. Setting up a storefront with great performance can feel daunting and time-consuming. There are many plugins, libraries, etc - the choice can be overwhelming.<p>Plus, in e-commerce, the backend and frontend are often written in different languages (e.g., PHP, Python, or Ruby for the backend). This increases the complexity and makes code management more challenging, especially for teams.<p>After working in e-commerce for several years, Michał and I set out to build the fastest and most compelling storefront for small to medium-sized merchants. Fast e-commerce sites are crucial because slow pages hurt sales [1]. Unfortunately, performance issues are still very common. The beauty of Your Next Store is its simplicity. No additional tools and no databases - just Next.js and Stripe.<p>On the technical side, we use App Router, React Server Component, Partial Pre-Rendering, Optimistic Updates, and Streaming with Suspense to make the store faster and leaner so it feels almost like a static website.<p>In summary:<p>Modern & Popular Stack: Built with Next.js, React.js, and TypeScript, making development faster and hiring easier compared to platforms that use less common frameworks like Shopify’s Liquid.<p>No Database Needed: Stripe handles the backend, reducing the need for complex infrastructure and simplifying the setup process.<p>Open Source: Free and open (AGPL), with the option for a commercial license if needed.<p>This is just the beginning. We want to make YNS even better and easier to use and eventually provide a good, open-source alternative to Shopify.<p>Check our code at <a href="https://github.com/yournextstore/yournextstore">https://github.com/yournextstore/yournextstore</a><p>We’d love to hear your thoughts and feedback! What features would you like to see next?<p>[1]: <a href="https://www.deloitte.com/ie/en/services/consulting/research/milliseconds-make-millions.html" rel="nofollow">https://www.deloitte.com/ie/en/services/consulting/research/...</a>
Show HN: YourNextStore – an open-source Shopify with Stripe as the back end
We’re building Your Next Store, a modern, ultra-fast, open-source commerce in Next.js with Stripe as the backend - no DB required.<p>Selling online is often more complex than it needs to be. Setting up a storefront with great performance can feel daunting and time-consuming. There are many plugins, libraries, etc - the choice can be overwhelming.<p>Plus, in e-commerce, the backend and frontend are often written in different languages (e.g., PHP, Python, or Ruby for the backend). This increases the complexity and makes code management more challenging, especially for teams.<p>After working in e-commerce for several years, Michał and I set out to build the fastest and most compelling storefront for small to medium-sized merchants. Fast e-commerce sites are crucial because slow pages hurt sales [1]. Unfortunately, performance issues are still very common. The beauty of Your Next Store is its simplicity. No additional tools and no databases - just Next.js and Stripe.<p>On the technical side, we use App Router, React Server Component, Partial Pre-Rendering, Optimistic Updates, and Streaming with Suspense to make the store faster and leaner so it feels almost like a static website.<p>In summary:<p>Modern & Popular Stack: Built with Next.js, React.js, and TypeScript, making development faster and hiring easier compared to platforms that use less common frameworks like Shopify’s Liquid.<p>No Database Needed: Stripe handles the backend, reducing the need for complex infrastructure and simplifying the setup process.<p>Open Source: Free and open (AGPL), with the option for a commercial license if needed.<p>This is just the beginning. We want to make YNS even better and easier to use and eventually provide a good, open-source alternative to Shopify.<p>Check our code at <a href="https://github.com/yournextstore/yournextstore">https://github.com/yournextstore/yournextstore</a><p>We’d love to hear your thoughts and feedback! What features would you like to see next?<p>[1]: <a href="https://www.deloitte.com/ie/en/services/consulting/research/milliseconds-make-millions.html" rel="nofollow">https://www.deloitte.com/ie/en/services/consulting/research/...</a>
Show HN: A directory of startups that did things that don't scale
Hey HN,<p>I've been working on a little side project and could really use your feedback.<p>So, I've always been fascinated by those stories of successful startups doing crazy things in their early days - you know, like Airbnb founders personally photographing listings or DoorDash founders delivering food themselves.<p>I started collecting these stories, and before I knew it, I had a pretty big list. So I thought, "Why not turn this into a website?" And that's how <a href="https://dothingsthatdontscale.org" rel="nofollow">https://dothingsthatdontscale.org</a> was born.<p>It's super basic right now - just a simple directory with about 70 examples. But I'm wondering if this could be useful for other founders or startup enthusiasts.<p>I'd love to hear your thoughts:<p>> Is this something you'd find helpful? Why or why not?<p>> What would make this more useful for you?<p>> Is it easy to use? (I'm not good at design)<p>> Am I missing any awesome stories that should be included?<p>I'm not trying to monetize this or anything - just want to create something helpful for the community. Any feedback, criticism, or ideas would be hugely appreciated!<p>Thanks in advance, you awesome people!
Show HN: What do your GitHub starred repos say about you?
Show HN: Open Message Format – a compact, vendor-agnostic spec for messages
Show HN: Io_uring for Ruby
Show HN: Io_uring for Ruby
Show HN: Io_uring for Ruby
Show HN: Ki Editor – Multicursor syntactical editor
Hi everyone, I have been developing this editor, Ki, for over a year, and have employed it substantially in all kinds of development (including Ki itself) for at least 3 months.<p>I think it is mostly crystallized, thus I'm happy to share it with you today.<p>Its main strength is first-class multi-cursor and structural (syntax) editing, which is a rare combination in the realm of editors (TUI or GUI alike).<p>Hope you'll enjoy it!
Show HN: Ki Editor – Multicursor syntactical editor
Hi everyone, I have been developing this editor, Ki, for over a year, and have employed it substantially in all kinds of development (including Ki itself) for at least 3 months.<p>I think it is mostly crystallized, thus I'm happy to share it with you today.<p>Its main strength is first-class multi-cursor and structural (syntax) editing, which is a rare combination in the realm of editors (TUI or GUI alike).<p>Hope you'll enjoy it!
Show HN: I mapped HN's favorite books with GPT-4o
Hey HN! I love finding new books to read on here. I wanted to gather the most mentioned books and recreate the serendipity of physical browsing. I scraped 20k comments from HN threads related to reading, extracted the references and opinions using GPT-4o mini, and visualised their embeddings as a map.<p>- OpenAI's embeddings were processed using UMAP and HDBSCAN. A direct 2D projection from the text embeddings didn't yield visually interesting results. Instead, HDBSCAN is first applied on a high-dimensional projection. Those clusters tend to correspond to different genres. The genre memberships are then embedded using a second round of UMAP (using Hellinger distance) which results in pleasingly dense structures.<p>- The books' descriptions are based on extractions from the comments and GPT's general knowledge. Quality levels vary, and it leads to some oddly specific points, but I haven't found any yet that are straight up wrong.<p>- There are multiple books with the same title. Currently, only the most popular one of those makes it onto the map.<p>- It's surprisingly hard to get high quality book cover images. I tried Google Books and a bunch of open APIs, but they all had their issues. In the end, I got the covers from GoodReads through a hacked together process that combines their autocomplete search with GPT for data linkage. Does anyone know of a reliable source?
Show HN: I mapped HN's favorite books with GPT-4o
Hey HN! I love finding new books to read on here. I wanted to gather the most mentioned books and recreate the serendipity of physical browsing. I scraped 20k comments from HN threads related to reading, extracted the references and opinions using GPT-4o mini, and visualised their embeddings as a map.<p>- OpenAI's embeddings were processed using UMAP and HDBSCAN. A direct 2D projection from the text embeddings didn't yield visually interesting results. Instead, HDBSCAN is first applied on a high-dimensional projection. Those clusters tend to correspond to different genres. The genre memberships are then embedded using a second round of UMAP (using Hellinger distance) which results in pleasingly dense structures.<p>- The books' descriptions are based on extractions from the comments and GPT's general knowledge. Quality levels vary, and it leads to some oddly specific points, but I haven't found any yet that are straight up wrong.<p>- There are multiple books with the same title. Currently, only the most popular one of those makes it onto the map.<p>- It's surprisingly hard to get high quality book cover images. I tried Google Books and a bunch of open APIs, but they all had their issues. In the end, I got the covers from GoodReads through a hacked together process that combines their autocomplete search with GPT for data linkage. Does anyone know of a reliable source?
Show HN: I mapped HN's favorite books with GPT-4o
Hey HN! I love finding new books to read on here. I wanted to gather the most mentioned books and recreate the serendipity of physical browsing. I scraped 20k comments from HN threads related to reading, extracted the references and opinions using GPT-4o mini, and visualised their embeddings as a map.<p>- OpenAI's embeddings were processed using UMAP and HDBSCAN. A direct 2D projection from the text embeddings didn't yield visually interesting results. Instead, HDBSCAN is first applied on a high-dimensional projection. Those clusters tend to correspond to different genres. The genre memberships are then embedded using a second round of UMAP (using Hellinger distance) which results in pleasingly dense structures.<p>- The books' descriptions are based on extractions from the comments and GPT's general knowledge. Quality levels vary, and it leads to some oddly specific points, but I haven't found any yet that are straight up wrong.<p>- There are multiple books with the same title. Currently, only the most popular one of those makes it onto the map.<p>- It's surprisingly hard to get high quality book cover images. I tried Google Books and a bunch of open APIs, but they all had their issues. In the end, I got the covers from GoodReads through a hacked together process that combines their autocomplete search with GPT for data linkage. Does anyone know of a reliable source?
Show HN: Automate API Testing with Record and Replay
This is shailendra here. Founder at HyperTest - hypertest.co<p>We are trying to make integration testing easy for developers. A lot of other teams and tools have taken a stab at this problem and having seen them we believe we have improvised the approach to help developers achieve this with minimum effort and pain.<p>How it works:
Developers set-up our SDK (2-lines) in the source code their (backend) services and configure it to record traffic from any environment. When HyperTest works in RECORD mode it collects end to end trace of every incoming request i.e. the request, response and outbound calls.<p>These requests (tests) can be replayed on a new build later (pre-push or at CI) to check for regressions in API responses and outbound calls. In the REPLAY mode HyperTest uses mocked responses of all dependent systems to keep tests non-flakey and results deterministic and consistent.
3-min demo - <a href="https://www.youtube.com/watch?v=x6hmDUNFGW4" rel="nofollow">https://www.youtube.com/watch?v=x6hmDUNFGW4</a><p>What does it do:
HyperTest SDK auto-instruments all key functions and methods across all libraries you use to make outbound calls. This helps HyperTest mock these calls in REPLAY without asking developers to make any change in their source code.<p>How is this better:
1. Set up is just like how you will set up an APM, i.e., 5 mins adding 2-lines of the SDK.<p>2. Support all protocols like http, graphQL, gRPC, Kafka and AMQP to cater to more use cases. Adding more as we speak<p>3. Test can be generated from any environment can be run anywhere even locally.<p>4. Active de-duplication to reduce the number of requests run on REPLAY. Optimise for code coverage & filter requests that don't cover additional lines of code<p>5. Distributed tracing to help developers debug root cause faster<p>6. Auto-updates mocks as dependencies change to keep test results trustworthy.<p>HyperTest is currently available only for node projects. We work the teams with 5 or more services at the moment and have 50+ teams using it actively.<p>If this seems valuable can set-up a quick intro and explain how to get started here -<a href="https://calendly.com/shailendra-hypertest/30min" rel="nofollow">https://calendly.com/shailendra-hypertest/30min</a><p>Would love feedback!
Show HN: SFTP Bridge to S3
Hey HN,<p>After seeing all the cool solopreneurs on X I decided to try and see for myself what this is all about. 9 months later here I am with my first project.<p>I decided to scratch my own itch, creating SFTP servers from a simple S3 bucket. I was tired of all my employer's customers asking for SFTP access when all I wanted was to use S3. There I have my lifecycle rules, proper access control, lambda triggers. All the cool stuff. But they keep asking for SFTP and let's be honest SFTP isn't cool.<p>So I created this bridge, they get SFTP, I get modern tech. I hope this tool can help you feel something when using SFTP too. Would love your feedback.<p>Paul-Henri
Show HN: DeutschlandAPI – A modern REST API to access information of Germany
Show HN: Dump entire Git repos into a single file for LLM prompts
Hey! I wanted to share a tool I've been working on. It's still very early and a work in progress, but I've found it incredibly helpful when working with Claude and OpenAI's models.<p>What it does:
I created a Python script that dumps your entire Git repository into a single file. This makes it much easier to use with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.<p>Key Features:
- Respects .gitignore patterns
- Generates a tree-like directory structure
- Includes file contents for all non-excluded files
- Customizable file type filtering<p>Why I find it useful for LLM/RAG:
- Full Context: It gives LLMs a complete picture of my project structure and implementation details.
- RAG-Ready: The dumped content serves as a great knowledge base for retrieval-augmented generation.
- Better Code Suggestions: LLMs seem to understand my project better and provide more accurate suggestions.
- Debugging Aid: When I ask for help with bugs, I can provide the full context easily.<p>How to use it:
Example: python dump.py /path/to/your/repo output.txt .gitignore py js tsx<p>Again, it's still a work in progress, but I've found it really helpful in my workflow with AI coding assistants (Claude/Openai). I'd love to hear your thoughts, suggestions, or if anyone else finds this useful!<p><a href="https://github.com/artkulak/repo2file">https://github.com/artkulak/repo2file</a><p>P.S. If anyone wants to contribute or has ideas for improvement, I'm all ears!
Show HN: Dump entire Git repos into a single file for LLM prompts
Hey! I wanted to share a tool I've been working on. It's still very early and a work in progress, but I've found it incredibly helpful when working with Claude and OpenAI's models.<p>What it does:
I created a Python script that dumps your entire Git repository into a single file. This makes it much easier to use with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.<p>Key Features:
- Respects .gitignore patterns
- Generates a tree-like directory structure
- Includes file contents for all non-excluded files
- Customizable file type filtering<p>Why I find it useful for LLM/RAG:
- Full Context: It gives LLMs a complete picture of my project structure and implementation details.
- RAG-Ready: The dumped content serves as a great knowledge base for retrieval-augmented generation.
- Better Code Suggestions: LLMs seem to understand my project better and provide more accurate suggestions.
- Debugging Aid: When I ask for help with bugs, I can provide the full context easily.<p>How to use it:
Example: python dump.py /path/to/your/repo output.txt .gitignore py js tsx<p>Again, it's still a work in progress, but I've found it really helpful in my workflow with AI coding assistants (Claude/Openai). I'd love to hear your thoughts, suggestions, or if anyone else finds this useful!<p><a href="https://github.com/artkulak/repo2file">https://github.com/artkulak/repo2file</a><p>P.S. If anyone wants to contribute or has ideas for improvement, I'm all ears!