5 Things I Wish I Knew Before Learning Streamlit

Would you like to understand the main limitations of the Streamlit Python library for building data web apps, before picking it up for a project?

In this video, I'll cruise through 5 obstacles that regularly come back within the community and multiple ways/hacks/techniques to work around those limits. You'll find out:
- how to hack markdown and iframe to style your app
- if it's possible to alter the Streamlit rerun event loop and Tornado Backend server
- thoughts to build a desktop app from your Streamlit app
- where is the ipywidgets integration into Streamlit at

After you watch me show you all those advanced techniques, you should have a good idea of Streamlit's limits and ways to go around Streamlit's "run from top to bottom philosophy" to meet your ends.

00:00 Intro
00:45 Fixed Branding
04:38 Looper
08:31 Hidden Tornado Server
12:17 Not an Executable
17:02 Refuse ipywidgets
20:30 Creativity in Constraints

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🔗 Links

- Is Streamlit useful: https://discuss.streamlit.io/t/is-streamlit-actually-useful/4125
- Partial reruns: https://github.com/streamlit/streamlit/issues/8022
- Using PyInstaller for Streamlit: https://discuss.streamlit.io/t/using-pyinstaller-or-similar-to-create-an-executable/902
- ipywidgets in Streamlit?: https://discuss.streamlit.io/t/ipywidgets-wip/3870

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🪶 "Instead of freaking out about these constraints, embrace them. Let them guide you. Constraints drive innovation and force focus. Instead of trying to remove them, use them to your advantage." - 37Signals, Getting Real: The Smarter, Faster, Easier Way to Build a Web Application

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#streamlit #python #datascience #dataapps