Streamlit is a framework in Python meant to turn data scripts into web apps in minutes. If you think about it, many apps are fundamentally data scripts first and web apps next. There are many scripts I have which would work better as simple web UIs.
I’ve been exploring how to get from idea to deployment quickly for a while. Of course, the answer is going to be slightly nuanced, but this approach works well for many simple and/or internal apps.
I recently launched CleanMail, which was actually a simple CLI tool back in 2019 called mail-sanitizer. However, it was using Google API credentials and was fairly inaccessible. Now I’ve moved it into a Streamlit app and deployed it on my Coolify instance, and people are using it frequently. I’ve also started migrating my scripts over to Streamlit since it’ll be easier to manage.
Here are some lessons I’ve learned while developing apps in Streamlit:
Embrace Forms
State management is hard, especially when there are no frameworks to rely on (like Redux, etc.). There is a lot of temptation to have independent elements in the UI and to manage state by hand. This will almost always end up being a bad idea.
Forms also control re-renders, and manual state management usually ends up being a pain in terms of the dreaded “Running” state, which kills the UX for the end user.
Minimize State to Manage
Forms help with this, but since there isn’t a lot of tooling around Streamlit right now, it’s important to minimize potential data present in state. Managing state and especially dependent variables in state is very prone to bugs.
Make Use of Fragments
Re-renders are time-consuming and sometimes irritating. Making use of the st.fragments API means that we can control the effects of state with more granularity. This becomes very important as the app scales up in logic.
If you haven’t used the st.fragments API, please do read about it. It’s quite handy.
LLMs for UI
Once all the core logic is in place, asking Aider to come up with an initial draft of UI is extremely useful. The first draft is surprisingly good and almost always close to what you would want in the end version.
Missing Components in the Ecosystem
Streamlit is awesome for a particular set of apps, but there are some critical components missing in my opinion. These are ordered by importance in my perspective
- Library for easily installing analytics like plausible, clarity etc..
- Libraries to simplify state management