[Python] How do I filter a Sunburst Chart by clicking on one of the segments?

This question is adjacent to a previous question I asked about filtering a table by clicking on a bar segment. I'd like to do the same thing with a sunburst, but don't seem to be able to get the callback to fire off with with on_click or on_hover.

• 
  I have set up sunburst_chart() in the server function that cycles through traces (there appears to be only one trace for this type of chart)
  
  
• 
  Each trace has on_click and on_hover applied with callback instructions to execute setHoverValues and setClickValues respectively.
  
  
• 
  setHoverValues() and setClickValues() each dump the value of the callback attribute 'points' into a reactive value.
  
  
• 
  The reactive values is display as a text widget.
  

I've tried to set breakpoints on the trace.on_hover() and trace.on_click(), and they stop once during program execution, but don't stop there again. Setting breakpoints anywhere inside setHoverValues() or setClickValues() doesn't do anything -- execution never stops there.

from shiny import App, reactive, render, ui
from shinywidgets import output_widget, render_widget
import plotly.graph_objects as go
import plotly.express as px
import pandas as pd

df=pd.DataFrame({'Category':['Utilities','Rent','Insurance','Gas','Parking','Maintenance','Groceries','Restaurants'],
'Category_L2':['Home','Home','Home','Car','Car','Car','Food','Food']})

app_ui = ui.page_fluid(
ui.output_text_verbatim('hoverInfoOutput'),
ui.output_text_verbatim('clickInfoOutput'),
output_widget('sunburst_chart'),
)


def server(input, output, session):

hoverInfo = reactive.value({})
clickInfo = reactive.value({})

def setHoverValues(trace, points, selector):
if not points.point_inds:
return
hoverInfo.set(points.copy())

@render.text
def hoverInfoOutput():
return hoverInfo.get()

def setClickValues(trace, points, selector):
if not points.point_inds:
return
clickInfo.set(points.copy())

@render.text
def clickInfoOutput():
return hoverInfo.get()

@render_widget
def sunburst_chart():
# Prepare data for the Sunburst chart
# We need labels, parents, values, and ids for each level

labels = []
parents = []
values = []
ids = []

# 1. Add Category_L2 (inner ring) data
# Count the occurrences of each Category_L2 to determine its size
l2_counts = df['Category_L2'].value_counts()

for l2_category, count in l2_counts.items():
labels.append(l2_category)
parents.append("") # Category_L2 are root parents for this hierarchy
values.append(count)
ids.append(f"L2_{l2_category}") # Unique ID for each L2 category

# 2. Add Category (outer ring) data
# Each Category instance contributes a value of 1 to its parent Category_L2
for index, row in df.iterrows():
category = row['Category']
category_l2 = row['Category_L2']
labels.append(category)
parents.append(f"L2_{category_l2}") # Parent is the corresponding Category_L2
values.append(1) # Each individual category entry has a value of 1
ids.append(f"Cat_{category}") # Unique ID for each Category

# Create the Plotly Sunburst chart
fig = go.Figure(go.Sunburst(
ids=ids,
labels=labels,
parents=parents,
values=values,
# Set the branch values to 'total' to ensure parent values are sums of children
branchvalues="total",
# Customize hover info
hovertemplate='<b>%{label}</b><br>Count: %{value}<extra></extra>',

))

# Update layout to make it a donut chart
fig.update_layout(
title_text='Two-Level Donut Chart: Category vs. Category_L2',
margin=dict(t=50, l=0, r=0, b=0), # Adjust margins for better fit
# Set the hole to create the donut effect (0.5 is a good starting point)
uniformtext_minsize=10, uniformtext_mode='hide' # Hide text if too small
)
figWidget = go.FigureWidget(fig)

for trace in fig.data:
trace.on_hover(setHoverValues)
trace.on_click(setClickValues)
return figWidget

app = App(app_ui, server)

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