This course will teach you how to develop web apps using the Streamlit library. With just a few lines of code, you can have your app up and running in no time.

streamlit.tar.gz

Streamlit

This course will teach you how to develop web apps using the Streamlit library. With just a few lines of code, you can have your app up and running in no time.

We'll start off with learning about the various components of Streamlit, before finally building an app that you can deploy and have your users access.

Develop Web Apps with Streamlit

Should you require your app users to upload files that will be involved in computation, you can use the file_uploader widget. By default, it allows you to upload files up to 200MB. This can be changed in configuration to suit your requirements. We'll explore Streamlit configuration later in this article.

You can specify the file types to upload. If no type is specified, all extensions can be uploaded.

file = st.file_uploader("Select a file to upload", type = ["csv", "txt"])

if file is not None:
    df = pd.read_csv(file)
    st.dataframe(df.sample(10))

First Things First

Introduction to Streamlit

Display Information with Streamlit

Display Interactive Widgets with Streamlit

Streamlit Layout

Mutate Data with Streamlit

Streamlit Miscallenous Items

Deploy Streamlit Apps

File Uploader with Streamlit