Передача данных Flask

import _thread
import asyncio
 
import matplotlib
import matplotlib.pyplot as plt
from flask import Flask, render_template, request, flash, jsonify, url_for
import json
import numpy as np
from app import app, db
x=None
y=None
@app.route("/")
def index():
    A = np.vstack([2 * x, 2 * y, np.ones(len(x))]).T
    b = x ** 2 + y ** 2
    center = np.linalg.lstsq(A, b, rcond=None)[0]
    # Находим центр окружности
    radius = np.sqrt(center[2] + center[0] ** 2 + center[1] ** 2)
    return render_template('index.html',radius=radius)
 
 
dct_point_coords = {}
 
 
@app.route("/get_data", methods=['POST'])
def get_data():
    lst_izvestatel = []  # Список извещателей,находящейся в области видимости
    data = request.get_json()
    dct_point_coords['coordinates'] = []
    y_min = request.json['wall_size'][1]
    y_max = 0
    x_min = request.json['wall_size'][0]
    x_max = 0
    for izvestatel in data['dct_izvestatel']:
        if izvestatel['yPosition'] < y_min:
            y_min = izvestatel['yPosition']
        if izvestatel['yPosition'] > y_max:
            y_max = izvestatel['yPosition']
        if izvestatel['xPosition'] < x_min:
            x_min = izvestatel['xPosition']
        if izvestatel['xPosition'] > x_max:
            x_max = izvestatel['xPosition']
        dct_point_coords['coordinates'].append(izvestatel)
        if izvestatel['xPosition'] > 0 and izvestatel['xPosition'] < request.json['wall_size'][0]:
            if izvestatel['yPosition'] > 0 and izvestatel['yPosition'] < request.json['wall_size'][1]:
                lst_izvestatel.append(izvestatel)
 
 
    print(len(lst_izvestatel))
 
    '''Вместо реализации k-среднего(ниже) выбран Метод Наименьшего Квадрата'''
    # x = np.array([point['xPosition'] for point in dct_point_coords['coordinates']])
    # x_reshaped = x.reshape(-1, 1)
    # y = np.array([point['yPosition'] for point in dct_point_coords['coordinates']])
    # y_reshaped = y.reshape(-1, 1)
    # clusterNum=3
    # k_means = KMeans(init='k-means++', n_clusters=clusterNum, n_init=12)
    # k_means.fit(np.hstack((x_reshaped, y_reshaped)))
    # labels=k_means.labels_
    # centers = k_means.cluster_centers_  # Coordinates of cluster centers.
    # plt.clf()  # Clear the current figure
    # plt.scatter(x=x, y=y, c=labels, s=50, cmap='viridis')
    # plt.scatter(centers[:, 0], centers[:, 1], c='red', s=150, alpha=1)
    """"""
    izveshatel_in_last_duge = data['dct_izvestatel'][-data['count_izveshatel_in_last_duge']:]
    x = np.array([i['xPosition'] for i in izveshatel_in_last_duge])
    y = np.array([i['yPosition'] for i in izveshatel_in_last_duge])
    return dct_point_coords
 
 
with app.app_context():
    db.create_all()