Deploying Streamlit with Streamlit Community Cloud

So far in this book, we have focused on Streamlit app development, from creating complex visualizations to deploying and creating Machine Learning (ML) models. In this chapter, we will learn how to deploy these applications so that they can be shared with anyone with internet access. This is a crucial part of Streamlit apps as, without the ability to deploy a Streamlit app, friction still exists for users or consumers of your work. If we believe that Streamlit removes the friction between creating data science analysis/products/models and sharing them with others, then we must also believe that the ability to widely share apps is just as crucial as the ease of development.

There are three main ways to deploy Streamlit apps: through a product created by Streamlit called Streamlit Community Cloud, through a cloud provider such as Amazon Web Services or Heroku, or through Hugging Face via Hugging Face Spaces. Deploying on AWS and...