Add selected_rows method to data frame renderer(#1121)

examples/dataframe/app.py

@@ -92,13 +92,10 @@ def handle_edit():
 
     @render.text
     def detail():
-        if (
-            input.grid_selected_rows() is not None
-            and len(input.grid_selected_rows()) > 0
-        ):
+        selected_rows = grid.input_selected_rows() or ()
+        if len(selected_rows) > 0:
             # "split", "records", "index", "columns", "values", "table"
-
-            return df().iloc[list(input.grid_selected_rows())]
+            return df().iloc[list(grid.input_selected_rows())]
 
 
 app = App(app_ui, server)

shiny/api-examples/data_frame/app-core.py

@@ -44,9 +44,11 @@ def summary_data():
 
     @reactive.calc
     def filtered_df():
-        # input.summary_data_selected_rows() is a tuple, so we must convert it to list,
+        req(summary_data.input_selected_rows())
+
+        # summary_data.selected_rows() is a tuple, so we must convert it to list,
         # as that's what Pandas requires for indexing.
-        selected_idx = list(req(input.summary_data_selected_rows()))
+        selected_idx = list(summary_data.input_selected_rows())
         countries = summary_df.iloc[selected_idx]["country"]
         # Filter data for selected countries
         return df[df["country"].isin(countries)]

shiny/api-examples/data_frame/app-express.py

@@ -3,7 +3,7 @@
 from shinywidgets import render_widget
 
 from shiny import reactive, req
-from shiny.express import input, render, ui
+from shiny.express import render, ui
 
 # Load the Gapminder dataset
 df = px.data.gapminder()
@@ -66,9 +66,12 @@ def country_detail_percap():
 
 @reactive.calc
 def filtered_df():
-    # input.summary_data_selected_rows() is a tuple, so we must convert it to list,
+    req(summary_data.input_selected_rows())
+
+    # summary_data.input_selected_rows() is a tuple, so we must convert it to list,
     # as that's what Pandas requires for indexing.
-    selected_idx = list(req(input.summary_data_selected_rows()))
+
+    selected_idx = list(summary_data.input_selected_rows())
     countries = summary_df.iloc[selected_idx]["country"]
     # Filter data for selected countries
     return df[df["country"].isin(countries)]

shiny/render/_dataframe.py

@@ -2,12 +2,22 @@
 
 import abc
 import json
-from typing import TYPE_CHECKING, Any, Literal, Protocol, Union, cast, runtime_checkable
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Literal,
+    Optional,
+    Protocol,
+    Union,
+    cast,
+    runtime_checkable,
+)
 
 from htmltools import Tag
 
 from .. import ui
 from .._docstring import add_example, no_example
+from ..session._utils import require_active_session
 from ._dataframe_unsafe import serialize_numpy_dtypes
 from .renderer import Jsonifiable, Renderer
 
@@ -237,8 +247,7 @@ class data_frame(Renderer[DataFrameResult]):
     Row selection
     -------------
     When using the row selection feature, you can access the selected rows by using the
-    `input.<id>_selected_rows()` function, where `<id>` is the `id` of the
-    :func:`~shiny.ui.output_data_frame`. The value returned will be `None` if no rows
+    `<data_frame_renderer>.input_selected_rows()` method, where `<data_frame_renderer>` is the render function name that corresponds with the `id=` used in :func:`~shiny.ui.outout_data_frame`. Internally, this method retrieves the selected row value from session's `input.<id>_selected_rows()` value. The value returned will be `None` if no rows
     are selected, or a tuple of integers representing the indices of the selected rows.
     To filter a pandas data frame down to the selected rows, use
     `df.iloc[list(input.<id>_selected_rows())]`.
@@ -270,6 +279,15 @@ async def transform(self, value: DataFrameResult) -> Jsonifiable:
             )
         return value.to_payload()
 
+    def input_selected_rows(self) -> Optional[tuple[int]]:
+        """
+        When `row_selection_mode` is set to "single" or "multiple" this will return
+        a tuple of integers representing the rows selected by a user.
+        """
+
+        active_session = require_active_session(None)
+        return active_session.input[self.output_id + "_selected_rows"]()
+
 
 @runtime_checkable
 class PandasCompatible(Protocol):

shiny/session/_session.py

@@ -214,9 +214,10 @@ def __init__(
 
         self._outbound_message_queues = OutBoundMessageQueues()
 
-        self._message_handlers: dict[str, Callable[..., Awaitable[object]]] = (
-            self._create_message_handlers()
-        )
+        self._message_handlers: dict[
+            str,
+            Callable[..., Awaitable[object]],
+        ] = self._create_message_handlers()
         self._file_upload_manager: FileUploadManager = FileUploadManager()
         self._on_ended_callbacks = _utils.AsyncCallbacks()
         self._has_run_session_end_tasks: bool = False
@@ -608,22 +609,26 @@ def _send_remove_ui(self, selector: str, multiple: bool) -> None:
     @overload
     def _send_progress(
         self, type: Literal["binding"], message: BindingProgressMessage
-    ) -> None: ...
+    ) -> None:
+        pass
 
     @overload
     def _send_progress(
         self, type: Literal["open"], message: OpenProgressMessage
-    ) -> None: ...
+    ) -> None:
+        pass
 
     @overload
     def _send_progress(
         self, type: Literal["close"], message: CloseProgressMessage
-    ) -> None: ...
+    ) -> None:
+        pass
 
     @overload
     def _send_progress(
         self, type: Literal["update"], message: UpdateProgressMessage
-    ) -> None: ...
+    ) -> None:
+        pass
 
     def _send_progress(self, type: str, message: object) -> None:
         msg: dict[str, object] = {"progress": {"type": type, "message": message}}
@@ -1033,7 +1038,8 @@ def __init__(
         self._suspend_when_hidden = suspend_when_hidden
 
     @overload
-    def __call__(self, renderer: RendererT) -> RendererT: ...
+    def __call__(self, renderer: RendererT) -> RendererT:
+        pass
 
     @overload
     def __call__(
@@ -1042,7 +1048,8 @@ def __call__(
         id: Optional[str] = None,
         suspend_when_hidden: bool = True,
         priority: int = 0,
-    ) -> Callable[[RendererT], RendererT]: ...
+    ) -> Callable[[RendererT], RendererT]:
+        pass
 
     def __call__(
         self,

tests/playwright/deploys/plotly/app.py

@@ -61,9 +61,11 @@ def summary_data():
 
     @reactive.Calc
     def filtered_df():
+        req(summary_data.input_selected_rows())
+
         # input.summary_data_selected_rows() is a tuple, so we must convert it to list,
         # as that's what Pandas requires for indexing.
-        selected_idx = list(req(input.summary_data_selected_rows()))
+        selected_idx = list(summary_data.input_selected_rows())
         countries = summary_df.iloc[selected_idx]["country"]
         # Filter data for selected countries
         return df[df["country"].isin(countries)]

tests/playwright/shiny/bugs/0676-row-selection/app.py

@@ -33,12 +33,9 @@ def grid():
 
     @render.table
     def detail():
-        if (
-            input.grid_selected_rows() is not None
-            and len(input.grid_selected_rows()) > 0
-        ):
-            # "split", "records", "index", "columns", "values", "table"
-            return df.iloc[list(input.grid_selected_rows())]
+        selected_rows = grid.input_selected_rows() or ()
+        if len(selected_rows) > 0:
+            return df.iloc[list(selected_rows)]
 
     @render.text
     def debug():