django-unicorn VS streamlit

Then there are stack-specific libraries: StimulusReflex for Rails, Phoenix LiveView, Laravel Livewire, Unicorn and Tetra for Django, Blazor for .NET, … and the list goes on.

- you get one of the best ORMs in existence with great relationship handling and generated admins

https://www.django-unicorn.com/

Not 1.0 yet but I'm using it in production and omgosh is it easy to crank out UIs.

There's a brilliant project called Django Unicorn that aims to be the equivalent of Laravel Livewire for Django. You should take a look.

https://www.django-unicorn.com/

That and HTMX + Alpine.js are a strong combination.

(I also had a bash at building a similar tool for Django called Tetra but unfortunately haven't had the time needed to commit to it: https://www.tetraframework.com)

I think all LiveView frameworks should be part of this.

Here are two Python ones I've tried:

https://www.django-unicorn.com/

I'm biased since I created https://www.django-unicorn.com/, but I have a few thoughts. :)

Have you looked into Django Unicorn?

Check out https://www.django-unicorn.com/ it is like htmx but is closer to Django.

When I was exploring the space, django-unicorn looked interesting also. But HTMX got me so far, so easily, that I didn't give unicorn a fair shake.

Developed using Langchain and Streamlit technologies for enhanced performance.

Hello,

Have you ever seen the https://streamlit.io/ ? I think this is what you are looking for.

While building dashboards in Streamlit, I found myself really missing Buefy's (Bulma) modern web components.

Specially due to the inability to add new values to Streamlit's multiselect [1], some missing controls like a polished image carousel [2] or a highly customizable data table.

Long story short, we put together streamfy (Streamlit + Buefy) as an MIT licensed project in GitHub to bring Buefy to Streamlit.

Demo: https://streamfy.streamlit.app

All the form components are implemented, missing half of other non-form UX components. There is plenty of room for PRs, testing, feedback, documentation, example, etc.

Please send issues and contributions to GitHub project [3] and general feedback to X / Twitter [4]

Thanks!

[1] https://github.com/streamlit/streamlit/issues/5348

Here's your savior, let's welcome Streamlit.

Looks cool. How do you see this differing from streamlit? https://streamlit.io/

Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance using your natural language. In this post, we will learn how to build a full-stack event-driven weather alert chat application in Python using pretty cool tools: Streamlit, NATS, and OpenAI. The app can collect real-time weather information, understand your criteria for alerts using AI, and deliver these alerts to the user interface.

In this tutorial, you'll construct a fully functional Streamlit application from the ground up. Streamlit lets you turn simple data scripts into web applications without traditional front-end tools. This application will be capable of downloading audio from any YouTube video, transcribing it using Deepgram, and then summarizing the content with the assistance of Mistral 7B, all streamlined through the capabilities of Langchain.

Install the Stable Diffusion tools and checkpoints, and run it all with Streamlit.