# Copyright (c) Streamlit Inc. (2018-2022) Snowflake Inc. (2022-2026) # # 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. from __future__ import annotations import json from dataclasses import dataclass from typing import ( TYPE_CHECKING, Any, Final, Literal, TypeAlias, Union, cast, overload, ) from streamlit import type_util from streamlit.deprecation_util import ( make_deprecated_name_warning, show_deprecation_warning, ) from streamlit.elements.lib.form_utils import current_form_id from streamlit.elements.lib.layout_utils import ( Height, LayoutConfig, Width, validate_height, validate_width, ) from streamlit.elements.lib.policies import check_widget_policies from streamlit.elements.lib.streamlit_plotly_theme import ( configure_streamlit_plotly_theme, ) from streamlit.elements.lib.utils import ( Key, compute_and_register_element_id, normalize_alt, to_key, ) from streamlit.errors import StreamlitValueError from streamlit.logger import get_logger from streamlit.proto.PlotlyChart_pb2 import PlotlyChart as PlotlyChartProto from streamlit.runtime.metrics_util import gather_metrics from streamlit.runtime.scriptrunner_utils.script_run_context import get_script_run_ctx from streamlit.runtime.state import ( WidgetCallback, register_widget, validate_on_change_mode, ) from streamlit.util import ReadOnlyAttributeDictionary if TYPE_CHECKING: from collections.abc import Iterable import plotly.graph_objs as go from matplotlib.figure import Figure as MatplotlibFigure from plotly.basedatatypes import BaseFigure from streamlit.delta_generator import DeltaGenerator # We need to configure the Plotly theme before any Plotly figures are created: configure_streamlit_plotly_theme() _AtomicFigureOrData: TypeAlias = Union[ "go.Figure", "go.Data", ] FigureOrData: TypeAlias = Union[ _AtomicFigureOrData, list[_AtomicFigureOrData], # It is kind of hard to figure out exactly what kind of dict is supported # here, as plotly hasn't embraced typing yet. This version is chosen to # align with the docstring. dict[str, _AtomicFigureOrData], "BaseFigure", "MatplotlibFigure", ] SelectionMode: TypeAlias = Literal["lasso", "points", "box"] _SELECTION_MODES: Final[set[SelectionMode]] = {"lasso", "points", "box"} _LOGGER: Final = get_logger(__name__) class PlotlySelectionState(ReadOnlyAttributeDictionary): """ The schema for the Plotly chart selection state. The selection state is stored in a read-only dictionary-like object that supports both key and attribute notation. Selection states cannot be programmatically changed or set through Session State. Attributes ---------- points : list[dict[str, Any]] The selected data points in the chart, including the data points selected by the box and lasso mode. The data includes the values associated to each point and a point index used to populate ``point_indices``. If additional information has been assigned to your points, such as size or legend group, this is also included. point_indices : list[int] The numerical indices of all selected data points in the chart. The details of each identified point are included in ``points``. box : list[dict[str, Any]] The metadata related to the box selection. This includes the coordinates of the selected area. lasso : list[dict[str, Any]] The metadata related to the lasso selection. This includes the coordinates of the selected area. Example ------- When working with more complicated graphs, the ``points`` attribute displays additional information. Try selecting points in the following example: >>> import plotly.express as px >>> import streamlit as st >>> >>> df = px.data.iris() >>> fig = px.scatter( ... df, ... x="sepal_width", ... y="sepal_length", ... color="species", ... size="petal_length", ... hover_data=["petal_width"], ... ) >>> >>> event = st.plotly_chart(fig, key="iris", on_select="rerun") >>> >>> event.selection .. output:: https://doc-chart-events-plotly-selection-state.streamlit.app height: 600px This is an example of the selection state when selecting a single point: >>> { >>> "points": [ >>> { >>> "curve_number": 2, >>> "point_number": 9, >>> "point_index": 9, >>> "x": 3.6, >>> "y": 7.2, >>> "customdata": [ >>> 2.5 >>> ], >>> "marker_size": 6.1, >>> "legendgroup": "virginica" >>> } >>> ], >>> "point_indices": [ >>> 9 >>> ], >>> "box": [], >>> "lasso": [] >>> } """ points: list[dict[str, Any]] point_indices: list[int] box: list[dict[str, Any]] lasso: list[dict[str, Any]] @overload def __getitem__(self, key: Literal["points"]) -> list[dict[str, Any]]: ... @overload def __getitem__(self, key: Literal["point_indices"]) -> list[int]: ... @overload def __getitem__(self, key: Literal["box"]) -> list[dict[str, Any]]: ... @overload def __getitem__(self, key: Literal["lasso"]) -> list[dict[str, Any]]: ... @overload def __getitem__(self, key: Any) -> Any: ... def __getitem__(self, key: Any) -> Any: return super().__getitem__(key) class PlotlyState(ReadOnlyAttributeDictionary): """ The schema for the Plotly chart event state. To use this type in an annotation, import it from ``streamlit.typing``. The event state is stored in a read-only dictionary-like object that supports both key and attribute notation. Event states cannot be programmatically changed or set through Session State. Only selection events are supported at this time. Attributes ---------- selection : dict The state of the ``on_select`` event. This attribute returns a dictionary-like object that supports both key and attribute notation. The attributes are described by ``PlotlySelectionState``. Example ------- Try selecting points by any of the three available methods (direct click, box, or lasso). The current selection state is available through Session State or as the output of the chart function. >>> import plotly.express as px >>> import streamlit as st >>> >>> df = px.data.iris() >>> fig = px.scatter(df, x="sepal_width", y="sepal_length") >>> >>> event = st.plotly_chart(fig, key="iris", on_select="rerun") >>> >>> event .. output:: https://doc-chart-events-plotly-state.streamlit.app height: 600px """ selection: PlotlySelectionState # ReadOnlyAttributeDictionary routes attribute access through __getitem__, # so the override below is enough to keep `selection` typed as # PlotlySelectionState. Use dict.__getitem__ for the selection key so the # read-only base class does not re-wrap the already-typed nested instance. @overload def __getitem__(self, key: Literal["selection"]) -> PlotlySelectionState: ... @overload def __getitem__(self, key: Any) -> Any: ... def __getitem__(self, key: Any) -> Any: if key == "selection": item = dict.__getitem__(self, key) if not isinstance(item, PlotlySelectionState): item = PlotlySelectionState(item) # Cache so repeated bracket/attribute access stays identity-stable. dict.__setitem__(self, key, item) return item return super().__getitem__(key) @dataclass class PlotlyChartSelectionSerde: """PlotlyChartSelectionSerde is used to serialize and deserialize the Plotly Chart selection state. """ def deserialize(self, ui_value: str | None) -> PlotlyState: empty_selection_state = PlotlyState( { "selection": PlotlySelectionState( { "points": [], "point_indices": [], "box": [], "lasso": [], } ), } ) if ui_value is None: return empty_selection_state parsed = json.loads(ui_value) if "selection" not in parsed: # pragma: no cover - defensive return empty_selection_state # Eagerly wrap selection so bracket access returns a stable typed # instance instead of creating a shallow copy on every access. parsed["selection"] = PlotlySelectionState(parsed["selection"]) return PlotlyState(parsed) def serialize(self, selection_state: PlotlyState) -> str: return json.dumps(selection_state, default=str) def parse_selection_mode( selection_mode: SelectionMode | Iterable[SelectionMode], ) -> set[PlotlyChartProto.SelectionMode.ValueType]: """Parse and check the user provided selection modes.""" if isinstance(selection_mode, str): # Only a single selection mode was passed selection_mode_set = {selection_mode} else: # Multiple selection modes were passed selection_mode_set = set(selection_mode) if not selection_mode_set.issubset(_SELECTION_MODES): raise StreamlitValueError( "selection_mode", [f"'{mode}'" for mode in sorted(_SELECTION_MODES)], ) parsed_selection_modes = [] for mode in selection_mode_set: if mode == "points": parsed_selection_modes.append(PlotlyChartProto.SelectionMode.POINTS) elif mode == "lasso": parsed_selection_modes.append(PlotlyChartProto.SelectionMode.LASSO) elif mode == "box": parsed_selection_modes.append(PlotlyChartProto.SelectionMode.BOX) return set(parsed_selection_modes) def _resolve_content_width(width: Width, figure: Any) -> Width: """Resolve "content" width by inspecting the figure's layout width. For content width, we check if the plotly figure has an explicit width in its layout. If so, we use that as a pixel width. If not, we default to 700 pixels which matches the plotly.js default width. Args ---- width : Width The original width parameter figure : Any The plotly figure object (Figure, dict, or other supported formats) Returns ------- Width The resolved width (either original width, figure width as pixels, or 700) """ if width != "content": return width # Extract width from the figure's layout # plotly.tools.mpl_to_plotly() returns Figure objects with .layout attribute # plotly.tools.return_figure_from_figure_or_data() returns dictionaries figure_width = None if isinstance(figure, dict): figure_width = figure.get("layout", {}).get("width") else: # Handle Figure objects from matplotlib conversion try: figure_width = figure.layout.width except (AttributeError, TypeError): _LOGGER.debug("Could not parse width from figure") if ( figure_width is not None and isinstance(figure_width, (int, float)) and figure_width > 0 ): return int(figure_width) # Default to 700 pixels (plotly.js default) when no width is specified return 700 def _resolve_content_height(height: Height, figure: Any) -> Height: """Resolve "content" height by inspecting the figure's layout height. For content height, we check if the plotly figure has an explicit height in its layout. If so, we use that as a pixel height. If not, we default to 450 pixels which matches the plotly.js default height. Args ---- height : Height The original height parameter figure : Any The plotly figure object (Figure, dict, or other supported formats) Returns ------- Height The resolved height (either original height, figure height as pixels, or 450) """ if height != "content": return height # Extract height from the figure's layout # plotly.tools.mpl_to_plotly() returns Figure objects with .layout attribute # plotly.tools.return_figure_from_figure_or_data() returns dictionaries figure_height = None if isinstance(figure, dict): figure_height = figure.get("layout", {}).get("height") else: # Handle Figure objects from matplotlib conversion try: figure_height = figure.layout.height except (AttributeError, TypeError): _LOGGER.debug("Could not parse height from figure") if ( figure_height is not None and isinstance(figure_height, (int, float)) and figure_height > 0 ): return int(figure_height) # Default to 450 pixels (plotly.js default) when no height is specified return 450 class PlotlyMixin: @overload def plotly_chart( self, figure_or_data: FigureOrData, use_container_width: bool | None = None, *, width: Width = "stretch", height: Height = "content", theme: Literal["streamlit"] | None = "streamlit", key: Key | None = None, on_select: Literal["ignore"] = "ignore", selection_mode: SelectionMode | Iterable[SelectionMode] = ( "points", "box", "lasso", ), config: dict[str, Any] | None = None, alt: str | None = None, ) -> DeltaGenerator: ... @overload def plotly_chart( self, figure_or_data: FigureOrData, use_container_width: bool | None = None, *, width: Width = "stretch", height: Height = "content", theme: Literal["streamlit"] | None = "streamlit", key: Key | None = None, # No default: omitted on_select must match the "ignore" overload. on_select: Literal["rerun"] | WidgetCallback, selection_mode: SelectionMode | Iterable[SelectionMode] = ( "points", "box", "lasso", ), config: dict[str, Any] | None = None, alt: str | None = None, ) -> PlotlyState: ... @gather_metrics("plotly_chart") def plotly_chart( self, figure_or_data: FigureOrData, use_container_width: bool | None = None, *, width: Width = "stretch", height: Height = "content", theme: Literal["streamlit"] | None = "streamlit", key: Key | None = None, on_select: Literal["rerun", "ignore"] | WidgetCallback = "ignore", selection_mode: SelectionMode | Iterable[SelectionMode] = ( "points", "box", "lasso", ), config: dict[str, Any] | None = None, alt: str | None = None, ) -> DeltaGenerator | PlotlyState: """Display an interactive Plotly chart. `Plotly `_ is a charting library for Python. To show Plotly charts in Streamlit, pass a Plotly ``Figure`` or ``Data`` object to ``st.plotly_chart``. .. Important:: You must install ``plotly>=4.0.0`` to use this command. Your app's performance may be enhanced by installing ``orjson`` as well. You can install all charting dependencies as an extra with Streamlit: .. code-block:: shell pip install streamlit[charts] Parameters ---------- figure_or_data : plotly.graph_objs.Figure, plotly.graph_objs.Data,\ or dict/list of plotly.graph_objs.Figure/Data The Plotly ``Figure`` or ``Data`` object to render. See https://plot.ly/python/ for examples of graph descriptions. .. note:: If your chart contains more than 1000 data points, Plotly will use a WebGL renderer to display the chart. Different browsers have different limits on the number of WebGL contexts per page. If you have multiple WebGL contexts on a page, you may need to switch to SVG rendering mode. You can do this by setting ``render_mode="svg"`` within the figure. For example, the following code defines a Plotly Express line chart that will render in SVG mode when passed to ``st.plotly_chart``: ``px.line(df, x="x", y="y", render_mode="svg")``. width : "stretch", "content", or int The width of the chart element. This can be one of the following: - ``"stretch"`` (default): The width of the element matches the width of the parent container. - ``"content"``: The width of the element matches the width of its content, but doesn't exceed the width of the parent container. - An integer specifying the width in pixels: The element has a fixed width. If the specified width is greater than the width of the parent container, the width of the element matches the width of the parent container. height : "content", "stretch", or int The height of the chart element. This can be one of the following: - ``"content"`` (default): The height of the element matches the height of its content. - ``"stretch"``: The height of the element matches the height of its content or the height of the parent container, whichever is larger. If the element is not in a parent container, the height of the element matches the height of its content. - An integer specifying the height in pixels: The element has a fixed height. If the content is larger than the specified height, scrolling is enabled. use_container_width : bool or None Whether to override the figure's native width with the width of the parent container. This can be one of the following: - ``None`` (default): Streamlit will use the value of ``width``. - ``True``: Streamlit sets the width of the figure to match the width of the parent container. - ``False``: Streamlit sets the width of the figure to fit its contents according to the plotting library, up to the width of the parent container. .. deprecated:: ``use_container_width`` is deprecated and will be removed in a future release. For ``use_container_width=True``, use ``width="stretch"``. theme : "streamlit" or None The theme of the chart. If ``theme`` is ``"streamlit"`` (default), Streamlit uses its own design default. If ``theme`` is ``None``, Streamlit falls back to the default behavior of the library. The ``"streamlit"`` theme can be partially customized through the configuration options ``theme.chartCategoricalColors`` and ``theme.chartSequentialColors``. Font configuration options are also applied. key : str, int, or None An optional string to use for giving this element a stable identity. If this is ``None`` (default), the element's identity will be determined based on the values of the other parameters. If selections are activated and ``key`` is provided, Streamlit will register the key in Session State to store the selection state. The selection state is read-only. For more details, see `Widget behavior `_. Additionally, if ``key`` is provided, it will be used as a CSS class name prefixed with ``st-key-``. on_select : "ignore" or "rerun" or callable How the figure should respond to user selection events. This controls whether or not the figure behaves like an input widget. ``on_select`` can be one of the following: - ``"ignore"`` (default): Streamlit will not react to any selection events in the chart. The figure will not behave like an input widget. - ``"rerun"``: Streamlit will rerun the app when the user selects data in the chart. In this case, ``st.plotly_chart`` will return the selection data as a dictionary. - A ``callable``: Streamlit will rerun the app and execute the ``callable`` as a callback function before the rest of the app. In this case, ``st.plotly_chart`` will return the selection data as a dictionary. selection_mode : "points", "box", "lasso" or an Iterable of these The selection mode of the chart. This can be one of the following: - ``"points"``: The chart will allow selections based on individual data points. - ``"box"``: The chart will allow selections based on rectangular areas. - ``"lasso"``: The chart will allow selections based on freeform areas. - An ``Iterable`` of the above options: The chart will allow selections based on the modes specified. All selections modes are activated by default. config : dict or None A dictionary of Plotly configuration options. This is passed to Plotly's ``show()`` function. For more information about Plotly configuration options, see Plotly's documentation on `Configuration in Python `_. alt : str or None A description of the chart for screen readers and other assistive technologies. If this is ``None`` (default), Streamlit does not provide an accessible name for the chart. An empty or whitespace-only string is treated the same as ``None`` and is logged so authors notice the dual meaning of ``alt=""`` across commands (decorative only on ``st.image`` / ``st.pyplot``). Prefer a short, specific description; a vague one can be worse than none. This is a short description of the chart, not a full text alternative for dense graphics. Returns ------- element or PlotlyState If ``on_select`` is ``"ignore"`` (default), this command returns an internal placeholder for the chart element. Otherwise, this command returns a ``PlotlyState`` object. This object is dictionary-like and supports both key and attribute notation. To use this type in an annotation, import it from ``streamlit.typing``. Examples -------- **Example 1: Basic Plotly chart** The example below comes from the examples at https://plot.ly/python. Note that ``plotly.figure_factory`` requires ``scipy`` to run. >>> import plotly.figure_factory as ff >>> import streamlit as st >>> from numpy.random import default_rng as rng >>> >>> hist_data = [ ... rng(0).standard_normal(200) - 2, ... rng(1).standard_normal(200), ... rng(2).standard_normal(200) + 2, ... ] >>> group_labels = ["Group 1", "Group 2", "Group 3"] >>> >>> fig = ff.create_distplot( ... hist_data, group_labels, bin_size=[0.1, 0.25, 0.5] ... ) >>> >>> st.plotly_chart( ... fig, alt="Distribution of three groups of random samples" ... ) .. output:: https://doc-plotly-chart.streamlit.app/ height: 550px **Example 2: Plotly Chart with configuration** By default, Plotly charts have scroll zoom enabled. If you have a longer page and want to avoid conflicts between page scrolling and zooming, you can use Plotly's configuration options to disable scroll zoom. In the following example, scroll zoom is disabled, but the zoom buttons are still enabled in the modebar. >>> import plotly.graph_objects as go >>> import streamlit as st >>> >>> fig = go.Figure() >>> fig.add_trace( ... go.Scatter( ... x=[1, 2, 3, 4, 5], ... y=[1, 3, 2, 5, 4] ... ) ... ) >>> >>> st.plotly_chart(fig, config = {'scrollZoom': False}) .. output:: https://doc-plotly-chart-config.streamlit.app/ height: 550px """ if use_container_width is not None: show_deprecation_warning( make_deprecated_name_warning( "use_container_width", "width", "2025-12-31", "For `use_container_width=True`, use `width='stretch'`. " "For `use_container_width=False`, use `width='content'`.", include_st_prefix=False, ), show_in_browser=False, ) if use_container_width: width = "stretch" elif not isinstance(width, int): width = "content" validate_width(width, allow_content=True) validate_height(height, allow_content=True) import plotly.io import plotly.tools # NOTE: "figure_or_data" is the name used in Plotly's .plot() method # for their main parameter. I don't like the name, but it's best to # keep it in sync with what Plotly calls it. if theme not in {"streamlit", None}: raise StreamlitValueError("theme", ["'streamlit'", "None"]) on_select_callback = validate_on_change_mode( on_select, supported_modes=("rerun", "ignore"), none_supported=False, param_name="on_select", ) key = to_key(key) is_selection_activated = on_select != "ignore" if is_selection_activated: # Run some checks that are only relevant when selections are activated is_callback = on_select_callback is not None check_widget_policies( self.dg, key, on_change=on_select_callback, default_value=None, writes_allowed=False, enable_check_callback_rules=is_callback, ) if type_util.is_type(figure_or_data, "matplotlib.figure.Figure"): # Convert matplotlib figure to plotly figure: figure = plotly.tools.mpl_to_plotly(figure_or_data) else: figure = plotly.tools.return_figure_from_figure_or_data( figure_or_data, validate_figure=True ) plotly_chart_proto = PlotlyChartProto() plotly_chart_proto.theme = theme or "" plotly_chart_proto.form_id = current_form_id(self.dg) config = config or {} plotly_chart_proto.spec = plotly.io.to_json(figure, validate=False) plotly_chart_proto.config = json.dumps(config) normalized_alt = normalize_alt(alt) if normalized_alt is not None: # Carry alt on its own proto field so it is not baked into the # wire spec JSON (frontend applies it as the chart accessible name). plotly_chart_proto.alt = normalized_alt ctx = get_script_run_ctx() # Compute an ID for every Plotly chart so the frontend can restore # state after remount. Always hash command kwargs (including alt), # even when the author set a key, so changing alt remounts the chart. plotly_chart_proto.id = compute_and_register_element_id( "plotly_chart", user_key=key, key_as_main_identity=False, dg=self.dg, plotly_spec=plotly_chart_proto.spec, plotly_config=plotly_chart_proto.config, selection_mode=selection_mode, is_selection_activated=is_selection_activated, theme=theme, width=width, height=height, alt=normalized_alt, ) # Handle "content" width and height by inspecting the figure's natural dimensions final_width = _resolve_content_width(width, figure) final_height = _resolve_content_height(height, figure) if is_selection_activated: # Selections are activated, treat plotly chart as a widget: plotly_chart_proto.selection_mode.extend( parse_selection_mode(selection_mode) ) serde = PlotlyChartSelectionSerde() widget_state = register_widget( plotly_chart_proto.id, on_change_handler=on_select_callback, deserializer=serde.deserialize, serializer=serde.serialize, ctx=ctx, value_type="string_value", ) layout_config = LayoutConfig(width=final_width, height=final_height) self.dg._enqueue( "plotly_chart", plotly_chart_proto, layout_config=layout_config ) return widget_state.value layout_config = LayoutConfig(width=final_width, height=final_height) return self.dg._enqueue( "plotly_chart", plotly_chart_proto, layout_config=layout_config ) @property def dg(self) -> DeltaGenerator: """The associated DeltaGenerator.""" return cast("DeltaGenerator", self)