render_widget now attaches it's return value to the decorated funct…

…ion (#119)

Co-authored-by: Barret Schloerke <[email protected]>

CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [UNRELEASED]
 
+* The `@render_widget` decorator now attaches a `widget` (and `value`) attribute to the function it decorates. This allows for easier access to the widget instance (or value), and eliminates the need for `register_widget` (which is now soft deprecated).  (#119)
 * Reduce default plot margins on plotly graphs.
 
 ## [0.2.4] - 2023-11-20

examples/altair/app.py

@@ -1,37 +1,24 @@
 import altair as alt
-from shiny import App, render, ui
+import shiny.express
+from shiny import render
 from vega_datasets import data
 
-from shinywidgets import output_widget, reactive_read, register_widget
+from shinywidgets import reactive_read, render_altair
 
-source = data.cars()
 
-app_ui = ui.page_fluid(
-    ui.output_text_verbatim("selection"),
-    output_widget("chart")
-)
+# Output selection information (click on legend in the plot)
+@render.text
+def selection():
+    pt = reactive_read(jchart.widget.selections, "point")
+    return "Selected point: " + str(pt)
 
-def server(input, output, session):
-
-    # Replicate JupyterChart interactivity
-    # https://altair-viz.github.io/user_guide/jupyter_chart.html#point-selections
+# Replicate JupyterChart interactivity
+# https://altair-viz.github.io/user_guide/jupyter_chart.html#point-selections
+@render_altair
+def jchart():
     brush = alt.selection_point(name="point", encodings=["color"], bind="legend")
-    chart = alt.Chart(source).mark_point().encode(
+    return alt.Chart(data.cars()).mark_point().encode(
         x='Horsepower:Q',
         y='Miles_per_Gallon:Q',
         color=alt.condition(brush, 'Origin:N', alt.value('grey')),
     ).add_params(brush)
-
-    jchart = alt.JupyterChart(chart)
-
-    # Display/register the chart in the app_ui
-    register_widget("chart", jchart)
-
-    # Reactive-ly read point selections
-    @output
-    @render.text
-    def selection():
-        pt = reactive_read(jchart.selections, "point")
-        return "Selected point: " + str(pt)
-
-app = App(app_ui, server)

examples/ipyleaflet/app.py

@@ -1,46 +1,36 @@
 import ipyleaflet as L
-from htmltools import css
-from shiny import *
-
-from shinywidgets import output_widget, reactive_read, register_widget
-
-app_ui = ui.page_fillable(
-    ui.div(
-        ui.input_slider("zoom", "Map zoom level", value=4, min=1, max=10),
-        ui.output_text("map_bounds"),
-        style=css(
-            display="flex", justify_content="center", align_items="center", gap="2rem"
-        ),
-    ),
-    output_widget("map"),
-)
-
-
-def server(input, output, session):
-
-    # Initialize and display when the session starts (1)
-    map = L.Map(center=(52, 360), zoom=4)
-    register_widget("map", map)
-
-    # When the slider changes, update the map's zoom attribute (2)
-    @reactive.Effect
-    def _():
-        map.zoom = input.zoom()
-
-    # When zooming directly on the map, update the slider's value (2 and 3)
-    @reactive.Effect
-    def _():
-        ui.update_slider("zoom", value=reactive_read(map, "zoom"))
-
-    # Everytime the map's bounds change, update the output message (3)
-    @output
-    @render.text
-    def map_bounds():
-        b = reactive_read(map, "bounds")
-        req(b)
-        lat = [b[0][0], b[0][1]]
-        lon = [b[1][0], b[1][1]]
-        return f"The current latitude is {lat} and longitude is {lon}"
+from shiny import reactive, render, req
+from shiny.express import input, ui
+
+from shinywidgets import reactive_read, render_widget
+
+ui.page_opts(title="ipyleaflet demo")
+
+with ui.sidebar():
+    ui.input_slider("zoom", "Map zoom level", value=4, min=1, max=10)
 
+@render_widget
+def lmap():
+    return L.Map(center=(52, 360), zoom=4)
 
-app = App(app_ui, server)
+# When the slider changes, update the map's zoom attribute
+@reactive.Effect
+def _():
+    lmap.widget.zoom = input.zoom()
+
+# When zooming directly on the map, update the slider's value
+@reactive.Effect
+def _():
+    zoom = reactive_read(lmap.widget, "zoom")
+    ui.update_slider("zoom", value=zoom)
+
+
+with ui.card(fill=False):
+    # Everytime the map's bounds change, update the output message
+    @render.ui
+    def map_bounds():
+        b = reactive_read(lmap.widget, "bounds")
+        req(b)
+        lat = [round(x) for x in [b[0][0], b[0][1]]]
+        lon = [round(x) for x in [b[1][0], b[1][1]]]
+        return f"The map bounds is currently {lat} / {lon}"

examples/ipywidgets/app.py

@@ -1,14 +1,13 @@
-import ipywidgets as ipy
-from ipywidgets.widgets.widget import Widget
-from shiny import *
+import shiny.express
+from ipywidgets import IntSlider
+from shiny import render
 
-from shinywidgets import *
+from shinywidgets import reactive_read, render_widget
 
-app_ui = ui.page_fluid(output_widget("slider"), ui.output_text("value"))
 
-
-def server(input: Inputs, output: Outputs, session: Session):
-    s: Widget = ipy.IntSlider(
+@render_widget
+def slider():
+    return IntSlider(
         value=7,
         min=0,
         max=10,
@@ -21,12 +20,7 @@ def server(input: Inputs, output: Outputs, session: Session):
         readout_format="d",
     )
 
-    register_widget("slider", s)
-
-    @output(id="value")
-    @render.text
-    def _():
-        return f"The value of the slider is: {reactive_read(s, 'value')}"
-
-
-app = App(app_ui, server, debug=True)
+@render.ui
+def slider_val():
+    val = reactive_read(slider.widget, "value")
+    return f"The value of the slider is: {val}"

examples/plotly/app.py

@@ -1,9 +1,10 @@
 import numpy as np
 import plotly.graph_objs as go
-from shiny import *
+from shiny import reactive
+from shiny.express import input, ui
 from sklearn.linear_model import LinearRegression
 
-from shinywidgets import output_widget, register_widget
+from shinywidgets import render_plotly
 
 # Generate some data and fit a linear regression
 n = 10000
@@ -13,15 +14,13 @@
 fit = LinearRegression().fit(x.reshape(-1, 1), dat[1])
 xgrid = np.linspace(start=min(x), stop=max(x), num=30)
 
-app_ui = ui.page_fillable(
-    ui.input_checkbox("show_fit", "Show fitted line", value=True),
-    output_widget("scatterplot"),
-)
+ui.page_opts(title="Plotly demo", fillable=True)
 
+ui.input_checkbox("show_fit", "Show fitted line", value=True)
 
-def server(input, output, session):
-
-    scatterplot = go.FigureWidget(
+@render_plotly
+def scatterplot():
+    return go.FigureWidget(
         data=[
             go.Scattergl(
                 x=x,
@@ -39,11 +38,7 @@ def server(input, output, session):
         layout={"showlegend": False},
     )
 
-    register_widget("scatterplot", scatterplot)
-
-    @reactive.Effect
-    def _():
-        scatterplot.data[1].visible = input.show_fit()
-
 
-app = App(app_ui, server)
+@reactive.Effect
+def _():
+    scatterplot.widget.data[1].visible = input.show_fit()

examples/pydeck/app.py

@@ -1,19 +1,16 @@
 import pydeck as pdk
-from shiny import *
+from shiny import reactive
+from shiny.express import input, ui
 
-from shinywidgets import *
+from shinywidgets import render_pydeck
 
-app_ui = ui.page_fillable(
-    ui.input_slider("zoom", "Zoom", 0, 20, 6, step=1),
-    output_widget("pydeck")
-)
-
-def server(input: Inputs, output: Outputs, session: Session):
+ui.input_slider("zoom", "Zoom", 0, 20, 6, step=1)
 
+@render_pydeck
+def deckmap():
     UK_ACCIDENTS_DATA = "https://raw.githubusercontent.com/visgl/deck.gl-data/master/examples/3d-heatmap/heatmap-data.csv"
-
     layer = pdk.Layer(
-        "HexagonLayer",  # `type` positional argument is here
+        "HexagonLayer",
         UK_ACCIDENTS_DATA,
         get_position=["lng", "lat"],
         auto_highlight=True,
@@ -23,7 +20,6 @@ def server(input: Inputs, output: Outputs, session: Session):
         extruded=True,
         coverage=1,
     )
-
     view_state = pdk.ViewState(
         longitude=-1.415,
         latitude=52.2323,
@@ -33,16 +29,9 @@ def server(input: Inputs, output: Outputs, session: Session):
         pitch=40.5,
         bearing=-27.36,
     )
+    return pdk.Deck(layers=[layer], initial_view_state=view_state)
 
-    deck = pdk.Deck(layers=[layer], initial_view_state=view_state)
-
-    # Register either the deck (or deck_widget) instance
-    register_widget("pydeck", deck)
-
-    @reactive.Effect()
-    def _():
-        deck.initial_view_state.zoom = input.zoom()
-        deck.update()
-
-
-app = App(app_ui, server)
+@reactive.effect()
+def _():
+    deckmap.value.initial_view_state.zoom = input.zoom()
+    deckmap.value.update()

setup.cfg

@@ -34,7 +34,8 @@ setup_requires =
 install_requires =
     ipywidgets>=7.6.5
     jupyter_core
-    shiny>=0.5.1.9003
+    # shiny>=0.6.1.9003
+    shiny @ git+https://github.com/posit-dev/py-shiny.git
     python-dateutil>=2.8.2
     # Needed because of https://github.com/python/importlib_metadata/issues/411
     importlib-metadata>=4.8.3,<5; python_version < "3.8"

shinywidgets/__init__.py

@@ -4,13 +4,32 @@
 __email__ = "[email protected]"
 __version__ = "0.2.4.9000"
 
+from ._as_widget import as_widget
 from ._dependencies import bokeh_dependency
-from ._shinywidgets import (
-    as_widget,
-    output_widget,
-    reactive_read,
-    register_widget,
+from ._output_widget import output_widget
+from ._render_widget import (
+    render_altair,
+    render_bokeh,
+    render_plotly,
+    render_pydeck,
     render_widget,
 )
+from ._shinywidgets import reactive_read, register_widget
 
-__all__ = ("output_widget", "register_widget", "render_widget", "reactive_read", "bokeh_dependency", "as_widget")
+__all__ = (
+    # Render methods first
+    "render_widget",
+    "render_altair",
+    "render_bokeh",
+    "render_plotly",
+    "render_pydeck",
+    # Reactive read second
+    "reactive_read",
+    # UI methods third
+    "output_widget",
+    # Other methods last
+    "as_widget",
+    "bokeh_dependency",
+    # Soft deprecated
+    "register_widget",
+)

shinywidgets/_as_widget.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from ipywidgets.widgets.widget import Widget
+from ipywidgets.widgets.widget import Widget  # pyright: ignore[reportMissingTypeStubs]
 
 from ._dependencies import widget_pkg
 
@@ -35,7 +35,7 @@ def as_widget(x: object) -> Widget:
 
 def as_widget_altair(x: object) -> Optional[Widget]:
     try:
-        from altair import JupyterChart
+        from altair import JupyterChart  # pyright: ignore[reportMissingTypeStubs]
     except ImportError:
         raise RuntimeError(
             "Failed to import altair.JupyterChart (do you need to pip install -U altair?)"
@@ -46,7 +46,7 @@ def as_widget_altair(x: object) -> Optional[Widget]:
 
 def as_widget_bokeh(x: object) -> Optional[Widget]:
     try:
-        from jupyter_bokeh import BokehModel
+        from jupyter_bokeh import BokehModel  # pyright: ignore[reportMissingTypeStubs]
     except ImportError:
         raise ImportError(
             "Install the jupyter_bokeh package to use bokeh with shinywidgets."
@@ -55,18 +55,19 @@ def as_widget_bokeh(x: object) -> Optional[Widget]:
     # TODO: ideally we'd do this in set_layout_defaults() but doing
     # `BokehModel(x)._model.sizing_mode = "stretch_both"`
     # there, but that doesn't seem to work??
-    from bokeh.plotting import figure
-    if isinstance(x, figure):
-        x.sizing_mode = "stretch_both"
+    from bokeh.plotting import figure  # pyright: ignore[reportMissingTypeStubs]
+
+    if isinstance(x, figure):  # type: ignore
+        x.sizing_mode = "stretch_both"  # pyright: ignore[reportGeneralTypeIssues]
 
     return BokehModel(x)  # type: ignore
 
 
 def as_widget_plotly(x: object) -> Optional[Widget]:
     # Don't need a try import here since this won't be called unless x is a plotly object
-    import plotly.graph_objects as go
+    import plotly.graph_objects as go  # pyright: ignore[reportMissingTypeStubs]
 
-    if not isinstance(x, go.Figure):
+    if not isinstance(x, go.Figure):  # type: ignore
         raise TypeError(
             f"Don't know how to coerce {x} into a plotly.graph_objects.FigureWidget object."
         )