Update slyder callback

Hello, I’m new to bokeh, I’m trying to plot an interactive map to display several clusters, but I can’t get to update the map with the slider due to an error on the python callback, I tried to use a JS callback but I don’t know the language.

#Define function that returns json_data for year selected by user.
    
def json_data(selectedMonth):
    Month = selectedMonth
    df_yr = Q4[Q4['variable'] == Month]
    Map_clusters_Q4 = Geometry.merge(ClustersQ4, how='outer', on=['MPIO_CNMBR'])
    Map_clusters_Q4_json = json.loads(Map_clusters_Q4.to_json())
    json_data = json.dumps(Map_clusters_Q4_json)
    return json_data

#Input GeoJSON source that contains features for plotting.
geosource = GeoJSONDataSource(geojson = json_data(9))

#Define a sequential multi-hue color palette.
palette = brewer['Spectral'][4]

#Instantiate LinearColorMapper that linearly maps numbers in a range, into a sequence of colors. Input nan_color.
color_mapper = LinearColorMapper(palette = palette, low = 1.0, high = 4.0, nan_color = '#d9d9d9')

#Define custom tick labels for color bar.
tick_labels = {'1': '1er Cuartil', '2': '2do Cuartil', '3':'3er Cuartil', '4':'4to Cuartil'}

#Add hover tool
hover = HoverTool(tooltips = [ ('Municipio','@MPIO_CNMBR'), ('Percentil', '@Clusters_Q4')])

#Create color bar. 
color_bar = ColorBar(color_mapper = color_mapper, label_standoff = 4, width = 500,
                     height = 15, border_line_color = None, location = (0,0), 
                     orientation = 'horizontal', major_label_overrides = tick_labels)

#Create figure object.
p = figure(title = 'Cluster Q4 mes 8',
           plot_height = 950 , plot_width = 950,
           toolbar_location = None, tools = [hover])

p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None

#Add patch renderer to figure. 
p.patches('xs','ys', source = geosource,fill_color = {'field' :'Clusters_Q4', 'transform' : color_mapper},
          line_color = 'black', line_width = 1, fill_alpha = 1)

p.add_layout(color_bar, 'below')

#Define the callback function: update_plot
def callback(attr, old, new):
    Month = slider.value
    new_data = json_data(Month)
    geosource.geojson = new_data
    p.title.text = 'Cluster Q4 mes %d' %Month

# Make a slider object: slider 
slider = Slider(title = 'Mes',start = 2, end = 9, step = 1, value = 9)
slider.on_change('value', callback)

# Make a column layout of widgetbox(slider) and plot, and add it to the current document
layout = column(p,slider)
curdoc().add_root(layout)

#Display plot inline in Jupyter notebook
output_notebook()

#Display plot
show(layout)

And I keep getting this error

image

Hi @marks5dawkins please edit your post to use code formatting so that the code is intelligible (either with the </> icon on the editing toolbar, or triple backtick ``` fences around the code blocks)

Edit: that said, the error you are getting attempts to be self-explanatory. If you want to use real python callbacks they you have to run a Bokeh server application. The Bokeh server is the Python process that would execute your Python callbacks. The link to learn more about Bokeh server applications is in the error message. There’s nothing I would start off saying here that isn’t already on that page.

Otherwise, if you just run regular Python code that calls show(obj) then you are generating self-contained HTML+JS output that has no connection to any running Python process, which means specifically: only JavaScript callbacks will be possible.

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You edited while I was editing, so ^^^ to make sure you see the additional comments

Also noting an example of embedding a Bokeh server app in a Jupyter notebook (since your code seems to be from a notebook) is here:

bokeh/notebook_embed.ipynb at branch-2.3 · bokeh/bokeh · GitHub

Thank you, Bryan.
As I said I new to bokeh, in the case of the JavaScript callbacks, I don’t know anything about the language so I’m struggling with designing the custom JS callback.

Looking at what you have above, I think it would be nontrivial to accomplish using JS callbacks. JS does not have any standard libraries like numpy or pandas, etc. so fancy indexing things like Q4[Q4['variable'] == Month] would have to be done manually by you with explicit looping. Also you would have to implement whatever all Geomtetry.merge does in JS as well. It would almost certainly be much easier to embed Bokeh server app in the notebook (see link above)

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