How to use Python libraries and functions in a C++ project

Question

I have two classes in a header in my C++ project, namely, Point_CCS_xy and class random_Point_CCS_xy_generator.

MWE

#include<iostream>
#include<fstream>
#include<functional>
#include<algorithm>
#include<deque>
#include<queue>
#include<set>
#include<list>
#include<limits>
#include<string>
#include<memory>
#include <iomanip>
#include <vector>
#include <random>

using namespace std;

class random_Point_CCS_xy_generator;
class Point_CCS_xy{
private:
    long double x_coordinate_ {0.0};
    long double y_coordinate_ {0.0};
public:
    Point_CCS_xy () = default;
    Point_CCS_xy(long double x, long double y);
    ~Point_CCS_xy() = default;
    // copy and move C-Tor and assignment plus some other setter getters come here    
    vector<Point_CCS_xy> Random_Point_CCS_xy(long double Min, long double Max, size_t n){
// uses function from class random_Point_CCS_xy_generator
}
};

What I want to do is :

1. Generate random points an return a vector of points ---> I already do that through this function : std::uniform_real_distribution<double> distribution_; and store them in a vector of points say vector<Point_CCS_xy> some_new_points(pnt2.Random_Point_CCS_xy(-5000, 5000, 50));

For instance, a vector of points of size 10:

some_new_points = [
[226.249243, 415.339357],
[94.324159, 15.358249],
[475.149262, 161.560577],
[28.652470, 288.493022],
[-425.899313, -170.149945],
[83.743814, -469.027833],
[428.593479, -480.247566],
[279.371955, -163.955121],
[-157.474035, -85.180488],
[407.313194, 151.480287]
]

2. Convert the vector some_new_points into an array using numpy

A = np.asarray([
    [226.249243, 415.339357],
    [94.324159, 15.358249],
    [475.149262, 161.560577],
    [28.652470, 288.493022],
    [-425.899313, -170.149945],
    [83.743814, -469.027833],
    [428.593479, -480.247566],
    [279.371955, -163.955121],
    [-157.474035, -85.180488],
    [407.313194, 151.480287]
    ])

3. Using scipy, like:

from scipy import spatial
import numpy as np
import time

A = np.asarray(
    [
         [226.249243, 415.339357],
         [94.324159, 15.358249],
         [475.149262, 161.560577],
         [28.652470, 288.493022],
         [-425.899313, -170.149945],
         [83.743814, -469.027833],
         [428.593479, -480.247566],
         [279.371955, -163.955121],
         [-157.474035, -85.180488],
         [407.313194, 151.480287]
    ]
)
pt = [20.45, 300.25]  # <-- the point to find
start = time.time()
distance, index = spatial.KDTree(A).query(pt)
print("distance: ", distance)
print("index: ", index)
print("A[index] = ", A[index])

4. Then, for instance using the returned index, from the original points vector some_new_points, I retrieve the point of interest.

Not that, I have already created a KD-Tree in my C++ program, but it does not have so many useful properties of that of scipy.spatial

I am newbie in programming and what I am currently doing seems to be primitive as I manually do the above steps.

My question is if I can directly make implement the functions in my .h header in the c++ Project without having to go through all those steps manually (from CLion to PyCharm). I would like to do the vector conversion and accessing KD-Tree of the scipy in my .h header file.