133 lines
4.6 KiB
Python
133 lines
4.6 KiB
Python
# Copyright (c) Streamlit Inc. (2018-2022) Snowflake Inc. (2022-2025)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""A Python wrapper around Bokeh."""
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from __future__ import annotations
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import json
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from typing import TYPE_CHECKING, Final, cast
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from streamlit.errors import StreamlitAPIException
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from streamlit.proto.BokehChart_pb2 import BokehChart as BokehChartProto
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from streamlit.runtime.metrics_util import gather_metrics
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from streamlit.util import calc_md5
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if TYPE_CHECKING:
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from bokeh.plotting.figure import Figure
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from streamlit.delta_generator import DeltaGenerator
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ST_BOKEH_VERSION: Final = "2.4.3"
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class BokehMixin:
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@gather_metrics("bokeh_chart")
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def bokeh_chart(
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self,
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figure: Figure,
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use_container_width: bool = True,
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) -> DeltaGenerator:
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"""Display an interactive Bokeh chart.
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Bokeh is a charting library for Python. The arguments to this function
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closely follow the ones for Bokeh's ``show`` function. You can find
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more about Bokeh at https://bokeh.pydata.org.
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To show Bokeh charts in Streamlit, call ``st.bokeh_chart``
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wherever you would call Bokeh's ``show``.
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.. Important::
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You must install ``bokeh==2.4.3`` and ``numpy<2`` to use this
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command.
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If you need a newer version of Bokeh, use our |streamlit-bokeh|_
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custom component instead.
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.. |streamlit-bokeh| replace:: ``streamlit-bokeh``
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.. _streamlit-bokeh: https://github.com/streamlit/streamlit-bokeh
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Parameters
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----------
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figure : bokeh.plotting.figure.Figure
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A Bokeh figure to plot.
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use_container_width : bool
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Whether to override the figure's native width with the width of
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the parent container. If ``use_container_width`` is ``True`` (default),
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Streamlit sets the width of the figure to match the width of the parent
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container. If ``use_container_width`` is ``False``, Streamlit sets the
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width of the chart to fit its contents according to the plotting library,
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up to the width of the parent container.
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Example
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-------
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>>> import streamlit as st
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>>> from bokeh.plotting import figure
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>>>
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>>> x = [1, 2, 3, 4, 5]
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>>> y = [6, 7, 2, 4, 5]
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>>>
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>>> p = figure(title="simple line example", x_axis_label="x", y_axis_label="y")
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>>> p.line(x, y, legend_label="Trend", line_width=2)
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>>>
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>>> st.bokeh_chart(p)
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.. output::
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https://doc-bokeh-chart.streamlit.app/
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height: 700px
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"""
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import bokeh
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if bokeh.__version__ != ST_BOKEH_VERSION:
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raise StreamlitAPIException(
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f"Streamlit only supports Bokeh version {ST_BOKEH_VERSION}, "
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f"but you have version {bokeh.__version__} installed. Please "
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f"run `pip install --force-reinstall --no-deps bokeh=="
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f"{ST_BOKEH_VERSION}` to install the correct version.\n\n\n"
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f"To use the latest version of Bokeh, install our custom component, "
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f"[streamlit-bokeh](https://github.com/streamlit/streamlit-bokeh)."
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)
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# Generate element ID from delta path
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delta_path = self.dg._get_delta_path_str()
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element_id = calc_md5(delta_path.encode())
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bokeh_chart_proto = BokehChartProto()
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marshall(bokeh_chart_proto, figure, use_container_width, element_id)
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return self.dg._enqueue("bokeh_chart", bokeh_chart_proto)
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@property
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def dg(self) -> DeltaGenerator:
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"""Get our DeltaGenerator."""
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return cast("DeltaGenerator", self)
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def marshall(
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proto: BokehChartProto,
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figure: Figure,
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use_container_width: bool,
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element_id: str,
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) -> None:
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"""Construct a Bokeh chart object.
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See DeltaGenerator.bokeh_chart for docs.
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"""
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from bokeh.embed import json_item
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data = json_item(figure)
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proto.figure = json.dumps(data)
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proto.use_container_width = use_container_width
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proto.element_id = element_id
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