How To Scrape Content With Load More Pages Using Selenium Python

I need to scrape the titles for all blog post articles via a Load More button as set by my desired range for i in range(1,3):

At present I’m only able to capture the titles for the first page even though i’m able to navigate to the next page using selenium.

Any help would be much appreciated.

from bs4 import BeautifulSoup
import pandas as pd
import requests
import time

# Selenium Routine
from requests_html import HTMLSession
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.action_chains import ActionChains

# Removes SSL Issues With Chrome
options = webdriver.ChromeOptions()
options.add_argument('--ignore-certificate-errors')
options.add_argument('--ignore-ssl-errors')
options.add_argument('--ignore-certificate-errors-spki-list')
options.add_argument('log-level=3') 
options.add_argument('--disable-notifications')
#options.add_argument('--headless') # Comment to view browser actions


# Get website url
urls = "https://jooble.org/blog/"
r = requests.get(urls)

driver = webdriver.Chrome(executable_path="C:webdriverschromedriver.exe",options=options)
driver.get(urls)

productlist = []

for i in range(1,3):
    
    # Get Page Information
    soup = BeautifulSoup(r.content, features='lxml')
    items = soup.find_all('div', class_ = 'post')
    print(f'LOOP: start [{len(items)}]')

    for single_item in items:
        title = single_item.find('div', class_ = 'front__news-title').text.strip()
        print('Title:', title)

        product = {
        'Title': title,
        }
        productlist.append(product)

    print()
    time.sleep(5)
    WebDriverWait(driver, 40).until(EC.element_to_be_clickable((By.XPATH,"//button[normalize-space()='Show more']"))).send_keys(Keys.ENTER)

driver.close()

# Save Results
df = pd.DataFrame(productlist)
df.to_csv('Results.csv', index=False)