在python中高效地计算数百万行的欧几里德距离

import numpy as np

# 生成随机数据
num_points = 1000000
data = np.random.rand(num_points, 2)

# 计算欧几里德距离
def euclidean_distance(point1, point2):
    return np.sqrt(np.sum((point1 - point2) ** 2))

distances = np.zeros((num_points, num_points))
for i in range(num_points):
    for j in range(i+1, num_points):
        distances[i, j] = euclidean_distance(data[i], data[j])
        distances[j, i] = distances[i, j]