@_with_element
def bokeh_chart(self, element, figure, use_container_width=False):
    "Display an interactive Bokeh chart.\n\n        Bokeh is a charting library for Python. The arguments to this function\n        closely follow the ones for Bokeh's `show` function. You can find\n        more about Bokeh at https://bokeh.pydata.org.\n\n        Parameters\n        ----------\n        figure : bokeh.plotting.figure.Figure\n            A Bokeh figure to plot.\n\n        use_container_width : bool\n            If True, set the chart width to the column width. This takes\n            precedence over Bokeh's native `width` value.\n\n        To show Bokeh charts in Streamlit, just call `st.bokeh_chart`\n        wherever you would call Bokeh's `show`.\n\n        Example\n        -------\n        >>> import streamlit as st\n        >>> from bokeh.plotting import figure\n        >>>\n        >>> x = [1, 2, 3, 4, 5]\n        >>> y = [6, 7, 2, 4, 5]\n        >>>\n        >>> p = figure(\n        ...     title='simple line example',\n        ...     x_axis_label='x',\n        ...     y_axis_label='y')\n        ...\n        >>> p.line(x, y, legend='Trend', line_width=2)\n        >>>\n        >>> st.bokeh_chart(p, use_container_width=True)\n\n        .. output::\n           https://share.streamlit.io/0.56.0-xTAd/index.html?id=Fdhg51uMbGMLRRxXV6ubzp\n           height: 600px\n\n        "
    import streamlit.elements.bokeh_chart as bokeh_chart
    bokeh_chart.marshall(element.bokeh_chart, figure, use_container_width)
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.

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.

To show Bokeh charts in Streamlit, just call `st.bokeh_chart`
wherever you would call Bokeh's `show`.

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='Trend', line_width=2)
>>>
>>> st.bokeh_chart(p, use_container_width=True)

.. output::
   https://share.streamlit.io/0.56.0-xTAd/index.html?id=Fdhg51uMbGMLRRxXV6ubzp
   height: 600px
@_with_element
def bokeh_chart(self, element, figure, use_container_width=False):
    "Display an interactive Bokeh chart.\n\n        Bokeh is a charting library for Python. The arguments to this function\n        closely follow the ones for Bokeh's `show` function. You can find\n        more about Bokeh at https://bokeh.pydata.org.\n\n        Parameters\n        ----------\n        figure : bokeh.plotting.figure.Figure\n            A Bokeh figure to plot.\n\n        use_container_width : bool\n            If True, set the chart width to the column width. This takes\n            precedence over Bokeh's native `width` value.\n\n        To show Bokeh charts in Streamlit, just call `st.bokeh_chart`\n        wherever you would call Bokeh's `show`.\n\n        Example\n        -------\n        >>> import streamlit as st\n        >>> from bokeh.plotting import figure\n        >>>\n        >>> x = [1, 2, 3, 4, 5]\n        >>> y = [6, 7, 2, 4, 5]\n        >>>\n        >>> p = figure(\n        ...     title='simple line example',\n        ...     x_axis_label='x',\n        ...     y_axis_label='y')\n        ...\n        >>> p.line(x, y, legend='Trend', line_width=2)\n        >>>\n        >>> st.bokeh_chart(p, use_container_width=True)\n\n        .. output::\n           https://share.streamlit.io/0.56.0-xTAd/index.html?id=Fdhg51uMbGMLRRxXV6ubzp\n           height: 600px\n\n        "
    import streamlit.elements.bokeh_chart as bokeh_chart
    bokeh_chart.marshall(element.bokeh_chart, figure, use_container_width)