streamlit VS dash

Streamlit: https://streamlit.io/

The agent uses MCP to translate this into a DynamoDB query. Then, using Streamlit UI, results are returned in a structured format, making it easy to use.

It's powered by something called "Streamlit" (https://streamlit.io).

> A faster way to build and share data apps

Website doesn't even load for me. I don't even know what to say...welcome to web dev 2025 edition.

Since Vaadin is Java-focused, its major benefits are best realized within that ecosystem. If you're using .NET, Blazor might be a better fit, while in the Python world, a lightweight alternative could be Streamlit.

We can embed this solution into a desktop client by creating a user interface using Streamlit to allow the user to interact with our RAG application via chat. Or you can make a Telegram bot, then it will be even easier to create an interface

Streamlit

I deployed a small dockerized app on GCP a couple months ago and these bots ended up costing me a ton of money for the stupidest reason: https://github.com/streamlit/streamlit/issues/9673

The majority of requests were from OpenAI…

This article aims to quickly get you started with the Python streamlit library, including installation, input data, chart drawing, basic controls, progress bars, and free deployment.

Streamlit makes it easy to create an interactive user interface (UI) for Python applications. In this section, you will build a simple, user-friendly interface where users can input a URL and display the scraped data.

Streamlit: Streamlit turns data scripts into shareable web apps in minutes.

Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.

You could use something like Streamlit or Dash. In any case you will be accessing your app through the browser.

Useful list. Dash & bokeh as two more in the space

https://github.com/plotly/dash

I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.

Plotly is a plotting library, and Dash is their open-source framework for building data apps with Python, R or Julia. (Dash also has an Enterprise version, but we'll focus on the open-source library here.)

Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.

looks like you can get it manually (albeit with a loss of interactivity) https://github.com/plotly/dash/issues/145

Shiny is a framework that makes it easy to build interactive web applications. Shiny was introduced 10 years ago as an R package. In his 10th anniversary keynote speech, Joe Cheng announced Shiny for Python at the 2022 RStudio Conference. Python programmers can now try out Shiny to create interactive data-driven web applications. Shiny comes as an alternative to other frameworks, like Dash, or Streamlit.