[Streamlit] Mastering Streamlit: Advanced Features for State, Interactive Plots, and Deployment

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Advanced Streamlit Features: State, Interactive Plots, and Deployment

Streamlit is a popular Python library for building web applications. It is known for its ease of use and its ability to create interactive and engaging applications.

In this blog post, we will discuss some advanced Streamlit features that can be used to create more sophisticated applications.

Using state in your app

One of the most powerful features of Streamlit is its ability to use state. State allows you to store data between user interactions. This can be used to keep track of the user’s progress, to remember their preferences, or to store any other data that you need to persist across interactions.

To use state in your app, you can use the st.session_state object. This object provides access to the current state of the app. You can use it to set, get, and delete state variables.

For example, the following code snippet sets a state variable called counter to 0 and then increments it by 1 each time the user clicks a button:

counter = st.session_state.counter
if counter is None:
  counter = 0

counter += 1

st.write(f"The counter is now {counter}")

Creating interactive plots

Streamlit also makes it easy to create interactive plots. You can use the st.plotly_chart and st.pyplot functions to create plots that can be interacted with by the user.

The st.plotly_chart function takes a Plotly figure as its argument and renders it in the app. The st.pyplot function takes a Matplotlib figure as its argument and renders it in the app.

For example, the following code snippet creates a simple line plot and allows the user to zoom and pan the plot:

import plotly.graph_objects as go

fig = go.Figure(
    data=[go.Line(x=[1, 2, 3], y=[4, 5, 6])],
    layout=go.Layout(title="Interactive Plot"),
)

st.plotly_chart(fig)

st_plotly_chart

Deploying your Streamlit app

Once you have created your Streamlit app, you can deploy it so that it can be accessed by others. There are a few different ways to deploy a Streamlit app.

One way to deploy a Streamlit app is to use the Streamlit Cloud service. Streamlit Cloud is a free service that allows you to deploy your app to the cloud with a single click.

Another way to deploy a Streamlit app is to use Docker. Docker is a tool that allows you to package your app into a container that can be run on any machine.

Finally, you can also deploy a Streamlit app to your own web server. This requires some technical knowledge, but it gives you the most control over your app.

Conclusion

These are just a few of the advanced features that Streamlit offers. With these features, you can create more sophisticated and interactive applications.

If you are interested in learning more about Streamlit, I recommend checking out the official documentation: https://docs.streamlit.io/

I hope this blog post was helpful.

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