How To: Panel with worker thread

Panel
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Thanks @Material-Scientist , @Jhsmit and @Marc . I suppose both Dask Client approaches should run faster than a simpler add_next_tick_callback approach? In bokeh discourse they suggest to use the add_next_tick_callback. I tried to perform similar task of this post.

import panel as pn, numpy as np
import holoviews as hv, pandas as pd
import asyncio
import time

from threading import Thread # Asyncio
from functools import partial
from holoviews.streams import Pipe, Buffer

pn.extension()
pn.config.sizing_mode = 'stretch_width'
hv.extension('bokeh')

# Example df for buffer
df = pd.DataFrame({"x":np.array([]),
                   "y":np.array([]),
                   "z":np.array([])}).set_index("x")

# Buffer that updates plot
buffer = Buffer(data=df)

# Some example scatter plot
dmap = hv.DynamicMap(hv.Scatter, 
                     streams=[buffer]).opts(bgcolor='black', 
                                            color='z', 
                                            show_legend=False, 
                                            width = 1200, height = 800,responsive=False
                                           )


@asyncio.coroutine
def update(x,y,z):
    buffer.send(pd.DataFrame({"x":x,"y":y,"z":z}).set_index("x"))
 

def blocking_task(doc):
     for i in range(100): 
        x = np.random.rand(1)
        y = np.random.rand(1)
        z = np.random.rand(1)
        # update the document from callback
        if doc:
            doc.add_next_tick_callback(partial(update,x=x,y=y,z=z))
        else:
            print('if not working', i)
     
    
def button_click(event):
    thread = Thread(target=partial(blocking_task, doc=pn.state.curdoc))
    thread.start()
    
    
btn = pn.widgets.Button(name='Run')    
btn.on_click(button_click)
    
    
p1 = pn.Column(btn, 
               pn.Row(dmap,  width = 1200, height = 800, sizing_mode="fixed")
              )    
p1.show('streaming hv')

Should i learn Dask or do the same thing?? What is the advantage of moving towards using dask despite its greater complexity?

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