Revert API changes made in Selected rows method #1121 (#1174)

examples/dataframe/app.py

@@ -92,10 +92,10 @@ def handle_edit():
 
     @render.text
     def detail():
-        selected_rows = grid.input_selected_rows() or ()
+        selected_rows = input.grid_selected_rows() or ()
         if len(selected_rows) > 0:
             # "split", "records", "index", "columns", "values", "table"
-            return df().iloc[list(grid.input_selected_rows())]
+            return df().iloc[list(input.grid_selected_rows())]
 
 
 app = App(app_ui, server)

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

@@ -44,11 +44,11 @@ def summary_data():
 
     @reactive.calc
     def filtered_df():
-        req(summary_data.input_selected_rows())
+        req(input.summary_data_selected_rows())
 
-        # summary_data.selected_rows() is a tuple, so we must convert it to list,
+        # 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(summary_data.input_selected_rows())
+        selected_idx = list(input.summary_data_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 render, ui
+from shiny.express import input, render, ui
 
 # Load the Gapminder dataset
 df = px.data.gapminder()
@@ -66,12 +66,12 @@ def country_detail_percap():
 
 @reactive.calc
 def filtered_df():
-    req(summary_data.input_selected_rows())
+    req(input.summary_data_selected_rows())
 
-    # summary_data.input_selected_rows() is a tuple, so we must convert it to list,
+    # 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(summary_data.input_selected_rows())
+    selected_idx = list(input.summary_data_selected_rows())
     countries = summary_df.iloc[selected_idx]["country"]
     # Filter data for selected countries
     return df[df["country"].isin(countries)]

shiny/render/_dataframe.py

@@ -2,22 +2,12 @@
 
 import abc
 import json
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Literal,
-    Optional,
-    Protocol,
-    Union,
-    cast,
-    runtime_checkable,
-)
+from typing import TYPE_CHECKING, Any, Literal, 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
 
@@ -248,7 +238,8 @@ class data_frame(Renderer[DataFrameResult]):
     Row selection
     -------------
     When using the row selection feature, you can access the selected rows by using the
-    `<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
+    `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
     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())]`.
@@ -267,6 +258,8 @@ class data_frame(Renderer[DataFrameResult]):
       objects you can return from the rendering function to specify options.
     """
 
+    # `<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
+
     def auto_output_ui(self) -> Tag:
         return ui.output_data_frame(id=self.output_id)
 
@@ -280,14 +273,14 @@ 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.
-        """
+    # 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"]()
+    #     active_session = require_active_session(None)
+    #     return active_session.input[self.output_id + "_selected_rows"]()
 
 
 @runtime_checkable

tests/playwright/deploys/plotly/app.py

@@ -61,11 +61,11 @@ def summary_data():
 
     @reactive.calc
     def filtered_df():
-        req(summary_data.input_selected_rows())
+        req(input.summary_data_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(summary_data.input_selected_rows())
+        selected_idx = list(input.summary_data_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

@@ -1,3 +1,7 @@
+from __future__ import annotations
+
+from typing import cast
+
 import pandas as pd
 
 from shiny import App, Inputs, Outputs, Session, render, ui
@@ -33,7 +37,7 @@ def grid():
 
     @render.table
     def detail():
-        selected_rows = grid.input_selected_rows() or ()
+        selected_rows = cast("tuple[int]", input.grid_selected_rows() or ())
         if len(selected_rows) > 0:
             return df.iloc[list(selected_rows)]