Metadata-Version: 2.1
Name: streamlit-analytics
Version: 0.0.1
Summary: Track & visualize user inputs to your streamlit app
Home-page: https://github.com/jrieke/streamlit-analytics
Author: Johannes Rieke
Author-email: johannes.rieke@gmail.com
License: MIT
Description: # streamlit-analytics
        
        **👀 Track & visualize user inputs to your streamlit app**
        
        This is a small extension for the fantastic [streamlit](https://www.streamlit.io/) 
        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.
        
        <p align="center">
            <img src="images/example.png" width=600>
        </p>
        
        
        ## Installation
        
        ```bash
        pip install git+https://github.com/jrieke/streamlit-analytics.git
        ```
        
        Requires Python 3.6+
        
        
        ## How to use it
        
        ```python
        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:
        
            ```python
            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. 
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Requires-Python: >=3.6
Description-Content-Type: text/markdown
