The best Hacker News stories from Show from the past day
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Show HN: ChatGPT Plugins are a security nightmare
Show HN: ChatGPT Plugins are a security nightmare
Show HN: Web demo of 13B Alpaca-LLaMA trained on improved Stanford dataset
Show HN: Datapane – A new way to build reports, dashboards, and apps in Python
Hello HN! We’re Leo and Mandeep, founders of Datapane (<a href="https://datapane.com" rel="nofollow">https://datapane.com</a>).<p>We're building a way to create reports, dashboards, and web apps from your existing data using Python. Think of it as a combination of React and htmx, specifically designed for the Python data stack.<p>Our GitHub is <a href="https://github.com/datapane/datapane">https://github.com/datapane/datapane</a> and you can try building a report or app in ~2 minutes on Codespaces: <a href="https://try.datapane.com" rel="nofollow">https://try.datapane.com</a><p>We started building Datapane at our previous start-up, where we struggled to deliver ML model results to clients. Much to our surprise, the data science took less time than repeatedly creating reports by copying and pasting plots into PowerPoint decks.<p>It seemed absurd that we had to switch to PowerPoint or legacy BI tools like Tableau to share, and our initial goal was to programmatically generate reports using the datasets and plots we had in Python. To enable this, we started hacking on a Python-based UI framework for constructing HTML views from data-centric blocks – like plots, data tables, and layout components.<p>You can export these to standalone HTML files, or host them as a web app on somewhere like GitHub Pages or Fly.io. We recently also added the ability to connect Python functions to forms and front-end events so you can build web apps which run backend code. We handle the entire network and RPC layer, so you only need to write plain Python functions that take parameters and return other blocks.<p>You can check out an example of the code to create a simple app: <a href="https://github.com/datapane/examples/blob/main/apps/iris-plotter/app.py">https://github.com/datapane/examples/blob/main/apps/iris-plo...</a><p>Datapane’s philosophy is pretty different from other products in the space.<p>We wanted to keep things simple, but avoid the footguns our users faced with frameworks like Streamlit, where the reactive/network-aware model was hard to move beyond an MVP or POC. For backend interactivity, we believe the original web got a lot right, and unlike reactive models which rely on websockets, Datapane is unashamedly request/response. This takes inspiration from HTTP and our own experiences with htmx, which offers an elegant way to add interactivity to HTML. Under the hood, we actually compile down to a (gasp!) XML-based hypermedia format, akin to HTML, but tailored specifically for constructing data UIs.<p>The result is that not every change in your app requires a server round trip, as much of it can be pre rendered and most interactivity happens on the client-side. In addition to improving performance, this also makes running in production become 10x simpler.<p>This separation between the view and backend compute also makes Datapane modular. If our app server isn’t a good fit for your use-case, serve Datapane views from the web-framework of your choice (we’ve been hacking on serving views from Django). Want to compute blocks from inside Airflow or generate them on a schedule or from a webhook? Computation can happen out of band of the UI. You can even build and host apps from inside of Jupyter, where you can preview blocks live and convert notebook cells to blocks in your view.<p>We currently offer a hosting platform on <a href="https://datapane.com" rel="nofollow">https://datapane.com</a> for sharing reports publicly (free) or with your team (paid), and will be adding serverless app hosting support to it in the next few weeks.<p>Our ultimate goal is to create an open-source toolkit for building data products across the entire stack – from reports, to dashboards, to full-stack apps – all using 100% Python. You can see a few we’ve built already in our gallery: <a href="https://datapane.com/gallery" rel="nofollow">https://datapane.com/gallery</a><p>We’d love to hear your feedback.<p>Thanks!
Show HN: Datapane – A new way to build reports, dashboards, and apps in Python
Hello HN! We’re Leo and Mandeep, founders of Datapane (<a href="https://datapane.com" rel="nofollow">https://datapane.com</a>).<p>We're building a way to create reports, dashboards, and web apps from your existing data using Python. Think of it as a combination of React and htmx, specifically designed for the Python data stack.<p>Our GitHub is <a href="https://github.com/datapane/datapane">https://github.com/datapane/datapane</a> and you can try building a report or app in ~2 minutes on Codespaces: <a href="https://try.datapane.com" rel="nofollow">https://try.datapane.com</a><p>We started building Datapane at our previous start-up, where we struggled to deliver ML model results to clients. Much to our surprise, the data science took less time than repeatedly creating reports by copying and pasting plots into PowerPoint decks.<p>It seemed absurd that we had to switch to PowerPoint or legacy BI tools like Tableau to share, and our initial goal was to programmatically generate reports using the datasets and plots we had in Python. To enable this, we started hacking on a Python-based UI framework for constructing HTML views from data-centric blocks – like plots, data tables, and layout components.<p>You can export these to standalone HTML files, or host them as a web app on somewhere like GitHub Pages or Fly.io. We recently also added the ability to connect Python functions to forms and front-end events so you can build web apps which run backend code. We handle the entire network and RPC layer, so you only need to write plain Python functions that take parameters and return other blocks.<p>You can check out an example of the code to create a simple app: <a href="https://github.com/datapane/examples/blob/main/apps/iris-plotter/app.py">https://github.com/datapane/examples/blob/main/apps/iris-plo...</a><p>Datapane’s philosophy is pretty different from other products in the space.<p>We wanted to keep things simple, but avoid the footguns our users faced with frameworks like Streamlit, where the reactive/network-aware model was hard to move beyond an MVP or POC. For backend interactivity, we believe the original web got a lot right, and unlike reactive models which rely on websockets, Datapane is unashamedly request/response. This takes inspiration from HTTP and our own experiences with htmx, which offers an elegant way to add interactivity to HTML. Under the hood, we actually compile down to a (gasp!) XML-based hypermedia format, akin to HTML, but tailored specifically for constructing data UIs.<p>The result is that not every change in your app requires a server round trip, as much of it can be pre rendered and most interactivity happens on the client-side. In addition to improving performance, this also makes running in production become 10x simpler.<p>This separation between the view and backend compute also makes Datapane modular. If our app server isn’t a good fit for your use-case, serve Datapane views from the web-framework of your choice (we’ve been hacking on serving views from Django). Want to compute blocks from inside Airflow or generate them on a schedule or from a webhook? Computation can happen out of band of the UI. You can even build and host apps from inside of Jupyter, where you can preview blocks live and convert notebook cells to blocks in your view.<p>We currently offer a hosting platform on <a href="https://datapane.com" rel="nofollow">https://datapane.com</a> for sharing reports publicly (free) or with your team (paid), and will be adding serverless app hosting support to it in the next few weeks.<p>Our ultimate goal is to create an open-source toolkit for building data products across the entire stack – from reports, to dashboards, to full-stack apps – all using 100% Python. You can see a few we’ve built already in our gallery: <a href="https://datapane.com/gallery" rel="nofollow">https://datapane.com/gallery</a><p>We’d love to hear your feedback.<p>Thanks!
Show HN: Use ChatGPT, Bing and Bard in one app
Show HN: Use ChatGPT, Bing and Bard in one app
Show HN: The Shark Programming Language
Show HN: The Shark Programming Language
Show HN: The Shark Programming Language
Show HN: GPT-4 autonomously editing a program allowing it to edit programs
Show HN: GPT-4 autonomously editing a program allowing it to edit programs
Show HN: GPT-4 autonomously editing a program allowing it to edit programs
Show HN: A structured list of jobs from “Who is hiring?”, parsed with GPT
Show HN: Moonshine – open-source, pretrained ML models for satellite
Hey HackerNews,<p>Today I'd like to share my open source project, Moonshine!<p>Pretrained vision models are a popular way to reduce how much data you need and to speed up training, but for remote sensing (i.e. aerial, satellite) it can be a challenge to find good weights. Why use Moonshine?<p>1. Pretrained on multispectral data: Existing popular CV packages are nice to use but are trained on ImageNet or similar, meaning that not only is the domain of the pretraining different, but you may be restricted to only 3 channels. For remote sensing platforms with multispectral data, this might be a non-starter. Moonshine includes models specifically trained for your remote sensing problems.<p>2. Focus on usability: There are academic releases of specialized models that do support remote sensing data, but often they are difficult to use. They might be hard to install, and often are supported by a grad student who is more focused on publication than software. A core tenant of Moonshine is that it should be easy to use.<p>I've been working on this project for nearly a year now and I'm really excited to show it off and most importantly get feedback! I have big plans for what to build in the future, but this set of features was the smallest one I could think of that would provide some value.<p>Docs: <a href="https://moonshineai.readthedocs.io/en/latest/index.html" rel="nofollow">https://moonshineai.readthedocs.io/en/latest/index.html</a>
Github: <a href="https://github.com/moonshinelabs-ai/moonshine">https://github.com/moonshinelabs-ai/moonshine</a>
Show HN: Remove “GPT” from your HN feed
Show HN: Dungeon Map Doodler Beta - Free online map drawing tool
This is a D&D map making tool I've been working on for a while now, but I just added some new features to the beta that I think HN users might find neat. When building a world map, you can use "Dynamic Brushes" to draw organic looking terrain. This is achieved entirely with svg filters and javascript canvas, no fancy libraries or anything. This came with a pretty large rewrite of some of the underlying code, so I'm sure there's a number of bugs I haven't come across, but I'd love to hear your opinions on it!
Show HN: Dungeon Map Doodler Beta - Free online map drawing tool
This is a D&D map making tool I've been working on for a while now, but I just added some new features to the beta that I think HN users might find neat. When building a world map, you can use "Dynamic Brushes" to draw organic looking terrain. This is achieved entirely with svg filters and javascript canvas, no fancy libraries or anything. This came with a pretty large rewrite of some of the underlying code, so I'm sure there's a number of bugs I haven't come across, but I'd love to hear your opinions on it!
Show HN: Dungeon Map Doodler Beta - Free online map drawing tool
This is a D&D map making tool I've been working on for a while now, but I just added some new features to the beta that I think HN users might find neat. When building a world map, you can use "Dynamic Brushes" to draw organic looking terrain. This is achieved entirely with svg filters and javascript canvas, no fancy libraries or anything. This came with a pretty large rewrite of some of the underlying code, so I'm sure there's a number of bugs I haven't come across, but I'd love to hear your opinions on it!