Introduction to Streamlit
Explore the basics of Streamlit, an open-source Python library designed to help you build web applications easily with minimal coding. This lesson guides you through installing and running Streamlit, interacting with demo apps, and understanding its value for data scientists who want to deploy models quickly without relying on complex frameworks or additional teams.
We'll cover the following...
What is Streamlit?
Streamlit is an open-source Python library that enables us to easily build a web application.
It’s ideal for data scientists that may want to do this without the complexity of a framework like Django or Flask or without the need to know front-end development.
We use just a few lines of code to make these web applications.
This ease of use means that data scientists can focus more on developing models that can be easily deployed rather than struggling to deploy the models. They also don’t need to rely on external teams to help them deploy these models.
Hello world!
Install Streamlit
To install Streamlit, we run the pip install streamlit command in a terminal window.
Run Streamlit
Once it’s installed, we run the streamlit hello command.
This opens a browser window that launches a demo application.
We click the “Click to launch app!” button below to launch the Streamlit application in a browser.
Explore the Streamlit demo
We can choose a demo from the browser window’s left panel and see what it does.
There are four different applications we can interact with to get a feel for what Streamlit has to offer.
These demos showcase several features that we’ll learn to build in future lessons. In the next lesson, we learn to display various kinds of information with Streamlit.