Slow dash server using interval

Hi. I am very new to dash, and I do not have a solid understanding of how it works, so any suggestions will help me here.

I created a fairly simple app to monitor some hardware output. This is simulated using the class DataObject.
I initialise a DataObject object for every component that is being monitored, and I pull data using the 2 functions spec_read and adc_get_samples. I then plot the data using a scatter plot and a histogram, for every object, and use and dcc.Interval to update all the plots every 10 seconds.

The issue is, the server is extremely slow, and the web browser uses a lot of CPU resources, for what I think is a simple process. Is there a way I can optimise this code? Thanks!

import plotly.graph_objects as go
from plotly.subplots import make_subplots

import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input,Output

import numpy as np
import time

class DataObject(object):
    def __init__(self, name, *args, **kwargs): = name
        self.nchans = 4096
        self.rms_x = 17.
        self.rms_y = 17.

    def adc_get_samples(self):
        x = np.random.normal(0, scale=self.rms_x, size=2*self.nchans).astype("int8")
        y = np.random.normal(0, scale=self.rms_y, size=2*self.nchans).astype("int8")
        return x,y

    def spec_read(self):
        xx = 10**(np.random.normal(size=self.nchans))
        yy = 10**(np.random.normal(size=self.nchans))
        return xx, yy

def get_x_data():
    return np.arange(4096)

obj_names = ['object1', 'object2', 'object3',
        'object4', 'object5', 'object6']

objects = [DataObject(obj_name) for obj_name in obj_names]

FIGS = {}
for obj in objects:
    fig = make_subplots(rows=1, cols=2,
            column_widths=[0.8, 0.2], horizontal_spacing=0.05,
            column_titles=['Spectra', 'ADC values'])

    x = get_x_data()
    xx,yy = obj.spec_read()
    adc_x, adc_y = obj.adc_get_samples()

	    'x': x,
	    'y': 10*np.log10(xx+0.1),
	    'name': 'X-pol',
	    'mode': 'lines+markers',
	    'type': 'scatter'
	}, 1, 1)
	    'x': x,
	    'y': 10*np.log10(yy+0.1),
	    'name': 'Y-pol',
	    'mode': 'lines+markers',
	    'type': 'scatter'
	}, 1, 1)

            go.Histogram(x=adc_x, name='', marker_color='blue'),
            1, 2)
            go.Histogram(x=adc_y, name='', marker_color='red'),
            1, 2)

            margin=dict(l=30, r=30, b=50, t=50),
            font = dict(family='Times new roman', size=20),
            annotations = dict(size=60)

    FIGS[] = fig

graphs = [dcc.Graph(figure=FIGS[obj_name], id=obj_name) for obj_name in obj_names]
FIGS_HTML = html.Div(graphs, id='figs_html')

app = dash.Dash()
app.layout = html.Div(
    [FIGS_HTML] +
        interval = 10*1000,
        n_intervals = 0)]

        [Output("figs_html", "children")],
        [Input("plot-update", "n_intervals")])
def gen_bp(interval=None):
    x = get_x_data()
    for i,obj in enumerate(objects):
        xx,yy = obj.spec_read()
        adc_x, adc_y = obj.adc_get_samples()
        FIGS_HTML.children[i][0].y = 10*np.log10(xx + 0.1)
        FIGS_HTML.children[i][0].x = x
        FIGS_HTML.children[i][1].y = 10*np.log10(yy + 0.1)
        FIGS_HTML.children[i][1].x = x

        FIGS_HTML.children[i][2].x = adc_x
        FIGS_HTML.children[i][2].name = 'RMS_x: %.2f' %np.std(adc_x)
        FIGS_HTML.children[i][3].x = adc_y
        FIGS_HTML.children[i][3].name = 'RMS_y: %.2f' %np.std(adc_y)

    return [FIGS_HTML.children]



Did you fixed your problem or no? because i have same issue and can’t understand what actual going on so please help me.