How to Run Selenium in Production with Flask Server?

I'm currently facing a challenge with deploying my Flask server application, which utilizes Selenium for web scraping, into a production environment. While I've successfully implemented Selenium for local development using ChromeWebDriver, I'm unsure about the best practices for Dockerizing it and deploying it in a production setting.

Here's a bit of background: I've built a Flask server that scrapes data from X's tweets ( formerly known as twitter ) using Selenium. However, as I prepare to deploy this application into production, I realize that I need guidance on how to effectively containerize it with Docker and manage the Selenium instances.

1. How can I Dockerize my Flask application along with Selenium dependencies to ensure seamless deployment in a production environment?
2. What are the best practices for managing Selenium instances within Docker containers?
3. Are there any specific configurations or optimizations I should consider for running Selenium in a production environment?

I'd appreciate any resources, blogs, or YouTube videos that provide insights into running Selenium in production environments with Flask servers. Whether it's documentation, tutorials, or personal experiences, any guidance would be helpful

from flask import Flask, render_template, request, jsonify
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import json
from time import sleep

app = Flask(__name__)


# Set the path to your chromedriver executable
chromedriver_path = '/path/to/chromedriver'

@app.route('/scrape', methods=['POST'])
def scrape():
    if request.method == 'POST':
        url = request.json.get('url')
        browser = webdriver.Chrome()

        # Initialize Chrome driver  
        try:
            # Navigate to the provided URL
            browser.get(url)
            # print(1)
            # Extract title and any other data you need
            tweet =  browser.find_element(By.XPATH, '//article[@data-testid="tweet"]')
            # print(2)
            element = WebDriverWait(browser,10).until(EC.presence_of_element_located((By.CLASS_NAME,'css-9pa8cd')))
            img = tweet.find_element(By.XPATH,'//img[@class="css-9pa8cd"]').get_attribute("src")
            # print(3)
            # print(img,"sujal")
            # print(4)
            # print(5)
            user_name_container = tweet.find_element(By.XPATH, '//a[@class="css-175oi2r r-1wbh5a2 r-dnmrzs r-1ny4l3l r-1loqt21"]')
            # print(6)
            user_name = user_name_container.get_attribute("href")[20:]
            # print(8)
            name_container = tweet.find_elements(By.XPATH, '//span[@class="css-1qaijid r-bcqeeo r-qvutc0 r-poiln3"]')
            name = name_container[6].text
            tweet_body = name_container[8].text
            time = tweet.find_element(By.TAG_NAME, 'time').text

            # print(time)
            # print(user_name)
            # Add more scraping logic as needed



            # Return the scraped data as JSON
            return jsonify({
                'user_name':user_name,
                'name':name,
                'tweet_body':tweet_body,
                'time':time,
                'img':img     
                })
        except Exception as e:
            # Handle any errors that may occur during scraping
            return jsonify({'error': str(e)})
        finally:
            # Make sure to close the driver even if an exception occurs
            pass

if __name__ == '__main__':
    app.run(debug=True)