### Install Streamlit Bokeh Events using Pip

Source: https://github.com/christophna/streamlit-bokeh3-events/blob/main/README_ash2shukla.md

This command installs the streamlit-bokeh-events package using pip. It's a prerequisite for using the component in your Streamlit applications.

```bash
pip install streamlit-bokeh-events
```

--------------------------------

### Install Streamlit Bokeh3 Events using Pip

Source: https://github.com/christophna/streamlit-bokeh3-events/blob/main/README.md

Installs the streamlit-bokeh3-events package, which is necessary for integrating Bokeh 3 plots with Streamlit applications. This command ensures all dependencies are managed automatically.

```bash
pip install streamlit-bokeh3-events
```

--------------------------------

### Python Usage of Streamlit Bokeh Events with Bokeh Plot

Source: https://github.com/christophna/streamlit-bokeh3-events/blob/main/README_ash2shukla.md

This Python code demonstrates how to integrate a Bokeh plot within a Streamlit application using the streamlit-bokeh-events component. It shows how to define custom JavaScript events on a Bokeh plot and capture their details within Streamlit. Dependencies include Streamlit and Bokeh.

```python
import streamlit as st
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource, CustomJS

# import function
from streamlit_bokeh_events import streamlit_bokeh_events

# create plot
p = figure(tools="lasso_select")
cds = ColumnDataSource(
    data={
        "x": [1, 2, 3, 4],
        "y": [4, 5, 6, 7],
    }
)
p.circle("x", "y", source=cds)

# define events
cds.selected.js_on_change(
    "indices",
    CustomJS(
        args=dict(source=cds),
        code='''
        document.dispatchEvent(
            new CustomEvent("YOUR_EVENT_NAME", {detail: {your_data: "goes-here"}})
        )
        '''
    )
)

# result will be a dict of {event_name: event.detail}
# events by default is "", in case of more than one events pass it as a comma separated values
# event1,event2 
# debounce is in ms
# refresh_on_update should be set to False only if we dont want to update datasource at runtime
# override_height overrides the viewport height
result = streamlit_bokeh_events(
        bokeh_plot=p,
        events="YOUR_EVENT_NAME",
        key="foo",
        refresh_on_update=False,
        override_height=600,
        debounce_time=500)

# use the result
st.write(result)
```

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