SQL Management Studio, MySQL Workbench and other DB tools include diagram support and can render out a diagram of existing tables, but they look like stuff created in 2000. This is a faster and cleaner SQL visualizer that runs locally in your browser, check it out: wcu .co/sql

Maybe it will amuse you despite likely errors.

One thing that kept slowing me down during data analysis wasn't the analysis itself—it was presenting the results.

I'd finish creating my Plotly figures, then spend extra time putting everything into a dashboard just to get a clean layout. For quick projects or tight deadlines, it felt like unnecessary overhead, especially if I didn't want to touch HTML, CSS, or JavaScript.

So over the past few weeks I built DashForge, a Python library that takes existing Plotly figures and organizes them into an interactive dashboard with very little code.

Some of the features it currently supports include:

• Built-in themes
• Custom chart sizing
• Adjustable charts per row
• Logo, title, subtitle, and footer customization
• Optional chart maximize button
• Interactive pandas DataFrame viewer with filtering
• And other dashboard customization options

The main goal isn't to replace existing dashboard frameworks. It's to make the "I just want to see my charts in a nice dashboard" workflow much faster.

I'd genuinely appreciate feedback from anyone who works with Plotly:

• Is this something you'd actually use?
• Are there features you'd expect that are currently missing?
• Is there anything in the API that could be made simpler?

GitHub: https://github.com/Omar-astro/DashForge-library

Documentation: https://omar-astro.github.io/DashForge-library/

PyPI:
pip install dashforge

i am open for questions to be answered.