in ipython widgets, how to update the dropdown widget with new value?

self.dropDown.value = 'Default'
self.dropDown.selected_label = 'Default'

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dbutils.widgets.help()

dbutils.widgets.help()

dbutils.widgets.dropdown("state", "CA", ["CA", "IL", "MI", "NY", "OR", "VA"])

dbutils.widgets.text("database", "customers_dev")

CREATE WIDGET DROPDOWN state DEFAULT "CA"
CHOICES SELECT * FROM(VALUES("CA"), ("IL"), ("MI"), ("NY"), ("OR"), ("VA"))

CREATE WIDGET TEXT database DEFAULT "customers_dev"

dbutils.widgets.dropdown("database", "default", [database[0]
   for database in spark.catalog.listDatabases()
])

dbutils.widgets.text("table", "")

dbutils.widgets.dropdown("database", "default", [database[0]
   for database in spark.catalog.listDatabases()
])

dbutils.widgets.text("table", "")

SHOW TABLES IN $ {
   database
}

SELECT *
   FROM $ {
      database
   }.$ {
      table
   }
LIMIT 100

# needed packages
import pandas as pd
import numpy as np
from ipywidgets
import widgets

# load data
df_london = pd.read_csv("data/international-visitors-london-raw.csv")

# get list of unique values with ALL string
ALL = 'ALL'
def unique_sorted_values_plus_ALL(array):
   unique = array.unique().tolist()
unique.sort()
unique.insert(0, ALL)
return unique

# initialize widgets
dropdown_year = widgets.Dropdown(options = unique_sorted_values_plus_ALL(df_london.year))
dropdown_purpose = widgets.Dropdown(options = unique_sorted_values_plus_ALL(df_london.purpose))
bounded_num = widgets.BoundedFloatText(min = 0, max = 100000, value = 5, step = 1)

# output widget
output = widgets.Output()

# set color of values in the data frame
def colour_ge_value(value, comparison):
   if value >= comparison:
   return 'color: red'
else:
   return 'color: black'

# filter data
def common_filtering(year, purpose, num):
   output.clear_output()

if (year == ALL) & (purpose == ALL):
   common_filter = df_london
elif year == ALL:
   common_filter = df_london[df_london.purpose == purpose]
elif purpose == ALL:
   common_filter = df_london[df_london.year == year]
else:
   common_filter = df_london[
      (df_london.year == year) & (df_london.purpose == purpose)
   ]

with output:
   print("Data set size", common_filter.shape)
display(
   common_filter.head(20).style.applymap(
      lambda x: colour_ge_value(x, num), subset = ["visits", "spend", "nights"]
   )
)

# define event handlers
def dropdown_year_eventhandler(change):
   common_filtering(change.new, dropdown_purpose.value, bounded_num.value)

def dropdown_purpose_eventhandler(change):
   common_filtering(dropdown_year.value, change.new, bounded_num.value)

def bounded_num_eventhandler(change):
   common_filtering(dropdown_year.value, dropdown_purpose.value, change.new)

# define observers
dropdown_year.observe(dropdown_year_eventhandler, names = "value")
dropdown_purpose.observe(dropdown_purpose_eventhandler, names = "value")
bounded_num.observe(bounded_num_eventhandler, names = "value")

# display input widgets
display(dropdown_year)
display(dropdown_purpose)
display(bounded_num)

# display output widget
display(output)

voila dashboard_ipywidgets.ipynb

def my_text_input_handler(attr, old, new):
   print("Previous label: " + old)
print("Updated label: " + new)

text_input = TextInput(value = "default", title = "Label:")
text_input.on_change("value", my_text_input_handler)

def my_radio_handler(new):
   print('Radio button option ' + str(new) + ' selected.')

radio_group = RadioGroup(labels = ["Option 1", "Option 2", "Option 3"], active = 0)
radio_group.on_click(my_radio_handler)

from bokeh.io
import show
from bokeh.models
import Button, CustomJS

button = Button(label = "Foo", button_type = "success")
button.js_on_click(CustomJS(code = "console.log('button: click!', this.toString())"))

show(button)

from bokeh.io
import show
from bokeh.models
import CheckboxButtonGroup, CustomJS

LABELS = ["Option 1", "Option 2", "Option 3"]

checkbox_button_group = CheckboxButtonGroup(labels = LABELS, active = [0, 1])
checkbox_button_group.js_on_click(CustomJS(code = ""
         "
         console.log('checkbox_button_group: active=' + this.active, this.toString())
         ""
         "))

         show(checkbox_button_group)

from bokeh.io
import show
from bokeh.models
import CheckboxGroup, CustomJS

LABELS = ["Option 1", "Option 2", "Option 3"]

checkbox_group = CheckboxGroup(labels = LABELS, active = [0, 1])
checkbox_group.js_on_click(CustomJS(code = ""
         "
         console.log('checkbox_group: active=' + this.active, this.toString())
         ""
         "))

         show(checkbox_group)

from bokeh.io
import show
from bokeh.layouts
import column
from bokeh.models
import ColorPicker
from bokeh.plotting
import Figure

plot = Figure(x_range = (0, 1), y_range = (0, 1), width = 350, height = 350)
line = plot.line(x = (0, 1), y = (0, 1), color = "black", line_width = 4)

picker = ColorPicker(title = "Line Color")
picker.js_link('color', line.glyph, 'line_color')

show(column(plot, picker))