Subscribe
Sign in
I think Streamlit is a great tool for building and sharing data apps. It's easy to use, even for people who don't have a lot of experience with front-end development. You can create beautiful, custom web apps in just a few minutes, and you can deploy them to the cloud with just a click. I've used Streamlit to build a few different data apps, and I've been really impressed with how easy it is to use. I've also been impressed with the community of Streamlit users. There are a lot of helpful people in the community who are willing to share their knowledge and help each other out. Overall, I think Streamlit is a great tool for anyone who wants to build and share data apps. It's easy to use, powerful, and has a great community. Here are some of the things I like about Streamlit: It's easy to use. Even if you don't have a lot of experience with front-end development, you can create beautiful, custom web apps in just a few minutes. It's powerful. Streamlit can be used to build a wide variety of data apps, from simple dashboards to complex machine learning models. It's fast. Streamlit apps are built in pure Python, so they're fast and efficient. It's deployable. Streamlit apps can be deployed to the cloud with just a click. It has a great community. There are a lot of helpful people in the Streamlit community who are willing to share their knowledge and help each other out.
Excellent tool to present and work with data easily, without worrying about layouts, css or HTML at all. It's also perfect to build a quick web interface to a python script.
A godsend. Our company's developing a local-first note taking app with a strong focus on NLP. We're training classifiers and taggers on all kinds of notes. For this purpose, we're developing a custom labelling pipeline, which up until yesterday was a CLI. After snooping around for a GUI solution that would match our requirements, I stumbled on Streamlit and it's pretty much everything we could hope for. In literally a good day of work, I have a little web app which non techie collaborators can use for labelling our data. Bravo!
