Streamlit Essentials

The following is based on the official Streamlit documentation source

Streamlit is a Python library for creating interactive web apps for data science and machine learning.
You build apps by adding Streamlit commands to a Python script and running it with streamlit run my_app.py.

Development Flow

Streamlit provides an interactive development loop: Write code, save, view results, and iterate.
Changes in your script trigger automatic updates in the app.
For a smooth development experience, arrange your code editor and app preview side by side.

Data Flow

Streamlit re-runs your entire script whenever changes occur in the source code or when users interact with app widgets.
Widgets are elements like sliders and buttons that enable user interaction.
Use the @st.cache_data decorator to optimize performance by skipping costly computations.

Display and Style Data

Streamlit supports displaying data in various ways, including text, tables, and charts.
You can use methods like st.write(), st.dataframe(), and st.table().
Customization options are available for styling data frames.

Widgets

Widgets are used to capture user input and display results.
Examples include:
- Slider: flipper_length = st.slider('Select a flipper length',min_value=160,max_value=240,step=5)
- Button: st.button('Press me!')
- Select Box: island = st.selectbox(label="Select an Island", options=['Dream','Torgersen', 'Biscoe']

Layout

You can organize widgets and content in a sidebar using st.sidebar.
st.columns() allows widgets to be displayed side by side.
Use st.expander to hide or show content and save space.

Progress and Themes

Show progress with st.progress() for long-running computations.
Streamlit supports light and dark themes, which you can customize in the settings.

Caching

Streamlit provides caching decorators to store and reuse the results of expensive function calls.
Use @st.cache_data for computations that return data and @st.cache_resource for global resources.

Multipage Apps

Organize large apps into multiple pages for easier management and navigation.
Create separate Python script files for each page and place them in a "pages" folder.
Each script corresponds to a different page in the app.

App Model

Streamlit apps are Python scripts that execute from top to bottom.
User interactions and changes trigger script reruns.
Caching is used to optimize performance and speed up app responses.

Next 🗿 Milestone

Well done 🎉!!! Time to start to build the Streamlit App