web2py VS streamlit

For reference, YouTube runs on Python[1,2,3]:

> 1. Python and Django: YouTube’s backend is predominantly written in Python, offering a balance of performance and readability.

> 2. Google Cloud Platform...

> 3. Java and C++: YouTube also utilizes Java and C++ for specific backend services, as they provide better performance for certain tasks.

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A long time ago, I looked into these Python frameworks:

- http://www.web2py.com/

- https://kivy.org/

[1]: https://blogopost.com/youtube-tech-stack/#backend

[2]: https://medium.com/@shanthanaroja99/technology-stack-behind-...

[3]: https://youtu.be/G-lGCC4KKok

At a previous job, not as a software developer, myself and a few others endeavoured to build a CRM for the church I worked at. We opted for web2py simply because it was the thing I had first learned after learning Python and had found incredible power in building something that people could use.

Its Github repository https://github.com/web2py/web2py although it was designed to reduce web development tasks such as developing web forms from starting and working like that. It is cross-platform means that you can run it on Windows, Linux, and other operating systems which can run on your computer.

Once mastered, frameworks like Django, Flask, Web2Py, and Bottle can significantly ease the life of a Python developer. Moreover, Python frameworks allow you to build an application prototype fast, as it essentially eliminates the need for repetitive input code.

Web2py

{{=T('Powered by')}} web2py

Streamlit (https://streamlit.io/)

Does it need to be live (i.e when database or underlying spreadsheet updates does it need to be reflected in real time on the dashboard) or are you ok with static display.

Live updating data is a pain I've messed around using javascript to force refresh html iframes on a timer. But I was never really satisfied with this. I've heard you can do things with websockets but that is starting to get too complicated for me (I'm not a programmer).

For static stuff one of the data scientists in my org pointed me to Streamlit (https://streamlit.io/) it's a python package I found very easy to use. Can easily combine SQL with CSV imports and display them all on one dashboard. Can use forms toggle butotns etc to control the display.

Note that there are many tools that make this easier/simpler to prototype, including chainlit, streamlit, etc… The backend API we built is amenable to interacting with them as well.

2.-Go to https://streamlit.io, log in, and create a new app from your GitHub repository.

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.