How to patch multiple pattern-matched elements?

Dash Python
1

Is there a way to patch multiple pattern-matched elements in a single callback?

For example:

import numpy as np
from dash import Patch, Input, Output, State

@app.callback(
    Output({'type': 'plot', 'index': ALL}, 'figure'}
    Input('trigger', 'data'}
    State({'type': 'plot', 'index': ALL}, 'figure'})
)
def update_plot_title_colors(trigger, figs):
   num_figs = len(figs)
   rgb_colors: [list(np.random.choice(range(256), size=3)) for _ in figs]
   
   patches = []  # what is the correct syntax for multiple patches?
   for rgb in rgb_colors:
        color = f"rgb({rgb[0]}, {rgb[1]}, {rgb[2]})"

        patched_figure = Patch()  # should location or parent be specified?
        patched_figure["layout"]["title"]["font"]["color"] = color
        patches.append(patched_figure)

   return patches

What is the correct syntax to patch multiple elements? Is this sort of functionality even supported?

2

Hi @s_g, welcome to the forums.

Did you actually try this? I think it should work.

3

Thanks for the welcome! I’m not sure what I did wrong before, but this does in fact work. I determined the best way to execute this type of callback is as follows:

import numpy as np
from dash import Patch, Input, Output, State
from dash.exceptions import PreventUpdate

@app.callback(
    Output({'type': 'plot', 'index': ALL}, 'figure'}
    Input('trigger', 'data'}
    State({'type': 'plot', 'index': ALL}, 'id'})
)
def update_plot_title_colors(trigger, plot_ids):
   if not plot_ids:
       raise PreventUpdate
   rgb_colors =[list(np.random.choice(range(256), size=3)) for _ in plot_ids]
   
   patches = []  
   for rgb in rgb_colors:
       color = f"rgb({rgb[0]}, {rgb[1]}, {rgb[2]})"

       patched_figure = Patch() 
       patched_figure["layout"]["title"]["font"]["color"] = color
       patches.append(patched_figure)

   return patches

Loading the State(component_proprty='id') is a better way to determine how many patches are needed (and potentially manipulate specific figures differently depending on their 'index') without the overhead of loading the entire figure.

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