docstr: Display an interactive Bokeh chart.
  
  Bokeh is a charting library for Python. The arguments to this function
  closely follow the ones for Bokeh's `show` function. You can find
  more about Bokeh at https://bokeh.pydata.org.
  
  To show Bokeh charts in Streamlit, call `st.bokeh_chart`
  wherever you would call Bokeh's `show`.
  
  Parameters
  ----------
  figure : bokeh.plotting.figure.Figure
      A Bokeh figure to plot.
  
  use_container_width : bool
      If True, set the chart width to the column width. This takes
      precedence over Bokeh's native `width` value.
  
  Example
  -------
  >>> import streamlit as st
  >>> from bokeh.plotting import figure
  >>>
  >>> x = [1, 2, 3, 4, 5]
  >>> y = [6, 7, 2, 4, 5]
  >>>
  >>> p = figure(
  ...     title='simple line example',
  ...     x_axis_label='x',
  ...     y_axis_label='y')
  ...
  >>> p.line(x, y, legend_label='Trend', line_width=2)
  >>>
  >>> st.bokeh_chart(p, use_container_width=True)
  
  .. output::
     https://doc-bokeh-chart.streamlit.app/
     height: 700px
code: def bokeh_chart(
      self,
      figure: "Figure",
      use_container_width: bool = False,
  ) -> "DeltaGenerator":
      """Display an interactive Bokeh chart.
  
      Bokeh is a charting library for Python. The arguments to this function
      closely follow the ones for Bokeh's `show` function. You can find
      more about Bokeh at https://bokeh.pydata.org.
  
      To show Bokeh charts in Streamlit, call `st.bokeh_chart`
      wherever you would call Bokeh's `show`.
  
      Parameters
      ----------
      figure : bokeh.plotting.figure.Figure
          A Bokeh figure to plot.
  
      use_container_width : bool
          If True, set the chart width to the column width. This takes
          precedence over Bokeh's native `width` value.
  
      Example
      -------
      >>> import streamlit as st
      >>> from bokeh.plotting import figure
      >>>
      >>> x = [1, 2, 3, 4, 5]
      >>> y = [6, 7, 2, 4, 5]
      >>>
      >>> p = figure(
      ...     title='simple line example',
      ...     x_axis_label='x',
      ...     y_axis_label='y')
      ...
      >>> p.line(x, y, legend_label='Trend', line_width=2)
      >>>
      >>> st.bokeh_chart(p, use_container_width=True)
  
      .. output::
         https://doc-bokeh-chart.streamlit.app/
         height: 700px
  
      """
      import bokeh
  
      if bokeh.__version__ != ST_BOKEH_VERSION:
          raise StreamlitAPIException(
              f"Streamlit only supports Bokeh version {ST_BOKEH_VERSION}, "
              f"but you have version {bokeh.__version__} installed. Please "
              f"run `pip install --force-reinstall --no-deps bokeh=="
              f"{ST_BOKEH_VERSION}` to install the correct version."
          )
  
      # Generate element ID from delta path
      delta_path = self.dg._get_delta_path_str()
  
      element_id = hashlib.md5(
          delta_path.encode(), **HASHLIB_KWARGS
      ).hexdigest()
      bokeh_chart_proto = BokehChartProto()
      marshall(
          bokeh_chart_proto, figure, use_container_width, element_id
      )
      return self.dg._enqueue("bokeh_chart", bokeh_chart_proto)
  
file_path: streamlit/lib/streamlit/elements/bokeh_chart.py
imports: import hashlib
  import json
  from typing import TYPE_CHECKING, cast
  from typing_extensions import Final
  from streamlit.errors import StreamlitAPIException
  from streamlit.proto.BokehChart_pb2 import BokehChart
  from streamlit.runtime.metrics_util import gather_metrics
  from streamlit.util import HASHLIB_KWARGS
label_desc: Use image node_id 1 for calling the BokehMixin obj's underlying member method code with example usage: obj.bokeh_chart(figure, use_container_width) and returns: self