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//  1. Import required Libraries
const express = require('express');
const passport = require('passport');
const session = require('express-session');
const { Issuer, Strategy } = require('openid-client');
const http = require("http");
require("dotenv").config();

//  2. Create an express application and setup session
const app = express();

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Here are the steps on how to save a model in Python using scikit-learn and use it in JavaScript:

1. Save model using joblib

import joblib

# Save the model
joblib.dump(model, "model.pkl")

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import numpy as np

# create the gradient decent fn
def gradient_descent(x, y):
  m_curr = b_curr = 0  #m and b current values
  iters = 1000
  lr = 0.009 #move on
  n = len(x)
  for i in range(iters):
    y_pred = m_curr * x + b_curr  #mx+b

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Apply the following transformations. (maybe lambda can help):

Gender: Encoded as 0 for Male and 1 for Female.
ProductCategory: Encoded as 1 for Electronics, 2 for Clothing, 3 for Groceries, and 4 for Cosmetics.
PaymentMethod: Encoded as 1 for Credit Card, 2 for Cash, and 3 for Debit Card.
MallBranch: Encoded as 1 for North, 2 for East, and 3 for West.

Keep rest columns as it is and dont create a new data frame

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import numpy as np
import pygame
from pygame.locals import *
from OpenGL.GL import *
from OpenGL.GLU import *
import random
import time

class Particle:
    def __init__(self, position, velocity, color, size, lifetime=10.0):

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# fixed code

import pygame
import random

# Initialize Pygame
pygame.init()

# Screen settings
SCREEN_WIDTH, SCREEN_HEIGHT = 800, 600