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Track & visualize user inputs to your streamlit app

Project description

streamlit-analytics

👀 Track & visualize user inputs to your streamlit app

This is a small extension for the fantastic streamlit framework. With just one line of code, it tracks and counts all user inputs to your streamlit app and visualizes the results directly in your browser. Think Google Analytics but for streamlit.

Installation

pip install git+https://github.com/jrieke/streamlit-analytics.git

Requires Python 3.6+

How to use it

import streamlit_analytics

with streamlit_analytics.track():
    st.text_input("Write something")
    st.button("Click me")

That's it! 🎈 All inputs & clicks will now be tracked and counted. Of course, you can also use any other streamlit component in the with block (currently supported: button, text_input, selectbox).

To view the results, append ?analytics=on to your app's URL (e.g. http://localhost:8501/?analytics=on). The results are then shown directly below your app (see image above).

More

  • You can password-protect your analytics results with streamlit_analytics.track(unsafe_password=...). The streamlit app will then ask you for this password. Do not choose an important password here – it is sent without encryption.

  • If you don't want a huge with block, you can also do:

    import streamlit_analytics
    
    streamlit_analytics.start_tracking()
    # your streamlit code here
    streamlit_analytics.stop_tracking()
    
  • Experimental: You can store analytics results as a json file by passing save_to_json="path/to/file.json" to streamlit_analytics.track or streamlit_analytics.stop_tracking. At the moment, this may lead to problems with concurrency if many users access the site at the same time.

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