team-10/env/Lib/site-packages/streamlit/elements/bokeh_chart.py
2025-08-02 07:34:44 +02:00

133 lines
4.6 KiB
Python

# Copyright (c) Streamlit Inc. (2018-2022) Snowflake Inc. (2022-2025)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""A Python wrapper around Bokeh."""
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Final, cast
from streamlit.errors import StreamlitAPIException
from streamlit.proto.BokehChart_pb2 import BokehChart as BokehChartProto
from streamlit.runtime.metrics_util import gather_metrics
from streamlit.util import calc_md5
if TYPE_CHECKING:
from bokeh.plotting.figure import Figure
from streamlit.delta_generator import DeltaGenerator
ST_BOKEH_VERSION: Final = "2.4.3"
class BokehMixin:
@gather_metrics("bokeh_chart")
def bokeh_chart(
self,
figure: Figure,
use_container_width: bool = True,
) -> 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``.
.. Important::
You must install ``bokeh==2.4.3`` and ``numpy<2`` to use this
command.
If you need a newer version of Bokeh, use our |streamlit-bokeh|_
custom component instead.
.. |streamlit-bokeh| replace:: ``streamlit-bokeh``
.. _streamlit-bokeh: https://github.com/streamlit/streamlit-bokeh
Parameters
----------
figure : bokeh.plotting.figure.Figure
A Bokeh figure to plot.
use_container_width : bool
Whether to override the figure's native width with the width of
the parent container. If ``use_container_width`` is ``True`` (default),
Streamlit sets the width of the figure to match the width of the parent
container. If ``use_container_width`` is ``False``, Streamlit sets the
width of the chart to fit its contents according to the plotting library,
up to the width of the parent container.
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)
.. 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.\n\n\n"
f"To use the latest version of Bokeh, install our custom component, "
f"[streamlit-bokeh](https://github.com/streamlit/streamlit-bokeh)."
)
# Generate element ID from delta path
delta_path = self.dg._get_delta_path_str()
element_id = calc_md5(delta_path.encode())
bokeh_chart_proto = BokehChartProto()
marshall(bokeh_chart_proto, figure, use_container_width, element_id)
return self.dg._enqueue("bokeh_chart", bokeh_chart_proto)
@property
def dg(self) -> DeltaGenerator:
"""Get our DeltaGenerator."""
return cast("DeltaGenerator", self)
def marshall(
proto: BokehChartProto,
figure: Figure,
use_container_width: bool,
element_id: str,
) -> None:
"""Construct a Bokeh chart object.
See DeltaGenerator.bokeh_chart for docs.
"""
from bokeh.embed import json_item
data = json_item(figure)
proto.figure = json.dumps(data)
proto.use_container_width = use_container_width
proto.element_id = element_id