How to use Streamlit and the implementation of its widgets

What is Streamlit?

Streamlit is an open source web application framework in Python. It is helpful in creating machine learning web applications in a given mean time. It is compatible with many Python libraries, namely:

• Keras
• Scikit-learn
• PyCaret
• Matplotlib
• Pandas
• Numpy

The command used to run a Streamlit web application is as follows:

streamlit run <yourscript.py>

Streamlit also has a cloud, where we can deploy our machine learning web applications. Anyone can access our application with the provided link.

Streamlit widgets

There are many widgets available in Streamlit that we can use to develop web applications. We will discuss some of these below.

Note: Streamlit encounters some issues when it is run with the Safari browser. So, we recommend the use of Google Chrome or Firefox.

Slider

Code explanation

• Line 1: We import streamlit.
• Line 2: We use the slider() function, and we assign the value of the slider to the variable value.
• Line 3: We print the value and its cube, which we select from the slider.

Dataframe table

Code explanation

• Lines 1–2: We import pandas and streamlit.

• Line 4: We set the title of our Streamlit web application using the title() method.

• Lines 8–13: We use the pandas Dataframe() function, along with the Streamlit write() function, to display the dataframe in a table.

Selectbox

Code explanation

• Line 1: We import streamlit.

• Line 3: We set the title of our Streamlit web application using the title() method.

• Lines 5–8: We use the selectbox() function. The first argument that we pass to the function is a string to display and the second argument is a list of options to select from.

• Line 9: We display the selected value using the write() function.

Checkbox

Code explanation

• Line 1: We import streamlit.

• Line 2: We set the title of our Streamlit web application using the title() method.

• Lines 3: We create a variable called checkbox that contains a boolean value.

• Lines 5–8: We write conditions for the values that we selected from the checkbox.

• Line 10: We display the selected value using the write() function.

Radio button

Code explanation

• Line 1: We import streamlit.

• Lines 2–4: We use the radio() function. The first argument that we pass to this function is a string to display and the second argument is a list of options to select from.

• Lines 6-9: We use conditions to display the value that is selected from the checkbox.

Sidebar

Code explanation

• Line 1: We import streamlit.

• Line 3: We set the title of our Streamlit web application using the title() method.

• Lines 5–8: We use the sidebar.selectbox() function. The first argument that we pass to the function is a string to display and the second argument is a list of options to select from.

• Line 9: We display the value that is selected from the sidebar selectbox.

Color picker

Code explanation

• Line 1: We import streamlit.
• Line 2: We use the color_picker() function to choose the color from the colors dialogue box.
• Line 3: We print the selected color value.