Slow performance with plotly chart builder

Hello all,
I need to use plotly as the backend of a microservice who generates charts dynamically.
Unfortunately, after a little benchmarking, I found that the plotly.express framework is very slow (around 5 secs to generate a chart from 500 lines dataset).

Here is the script I use to generate a scatter matrix:

import sys
import os
import traceback
import json
import time
sys.path.append('c:\\statwolf\\python\packages\Lib\site-packages')
input = json.loads('{\"file\":\"/tmp/data.tsv",\"color\":\"club_country\",\"dimensions\":[\"nolo\",\"tolo\",\"yolo\"]}')
def action():
    def run():
        import plotly.express as px
        from pandas import read_csv
    
        color = None if input['color'] == "" else input['color']
    
        first = time.time()
        d = read_csv(input['file'], sep='\t')
        second = time.time()
        fig = px.scatter_matrix(d, dimensions=input['dimensions'], color=color)
        third = time.time()
        j = fig.to_json()
        fourth = time.time()
    
        print('read: ' + str(second - first))
        print('plot: ' + str(third - second))
        print('json: ' + str(fourth - third))
        return j
    
    import time
    
    for i in range(0, 3):
        start = time.time()
        result = run()
        end = time.time()
    
        print('iteration: ' + str(i) + '\ntime: ' + str(end - start))
    
    return result
    
result = None
try:
    result = { 'outcome': action() }
except Exception as e:
    traceback.print_exc()
    result = { 'error': str(e) }
resultDir = os.path.dirname(os.path.realpath(__file__))
resultFile = open(resultDir + '/result.json', 'w')
json.dump(result, resultFile)
resultFile.close()

from the dataset:
https://www.dropbox.com/s/cm9i3pfv10exbba/data.tsv?dl=1

and this is the report with timing:
https://www.dropbox.com/s/l2x3jqzea4i4xqw/report.txt?dl=1

Now:

1. Is there any tweak I can implement to improve performances?
2. Do you plan to focus on speed for the following releases?

Commencez par réexécuter le script de benchmark fourni et examiner le rapport de temps lié, en séparant les temps de read_csv, plotly.express.scatter_matrix et fig.to_json. Suivez le point d’entrée de scatter-matrix ainsi que les tests de performance ou benchmarks existants ; la tâche serait considérée comme terminée s’il était nécessaire d’identifier un goulot d’étranglement reproductible et de convenir d’une amélioration mesurable, mais l’issue ne définit pas de cible d’acceptation.