run.py

from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from bs4 import BeautifulSoup
from webdriver_manager.chrome import ChromeDriverManager
import pandas as pd
import time

service = Service(ChromeDriverManager().install())
driver = webdriver.Chrome(service=service)

url = "https://www.laphil.com/events/performances"
driver.get(url)

# for scrolling
current_scroll_position = driver.execute_script("return window.pageYOffset;")
scroll_height = driver.execute_script("return document.body.scrollHeight;")
if current_scroll_position < scroll_height:
    driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
    time.sleep(1)
driver.implicitly_wait(10)

soup = BeautifulSoup(driver.page_source, "html.parser")
titles = soup.find_all(class_="info")

# # Dislay raw lines
# print(titles)
# for title in titles:
#    print(title.text.strip())


data = []
titles = soup.find_all(class_="info")
for title in titles:
    # bring title text
    title_text = title.find(class_="name name--short").get_text(strip=True)
    # bring supporting-acts text
    supporting_acts = title.find(class_="supporting-acts")
    supporting_acts_text = (
        supporting_acts.get_text(strip=True) if supporting_acts else ""
    )
    # parse text
    date_text = title.find(class_="date-text").get_text(strip=True)
    time_text = title.find(class_="time").get_text(strip=True).replace("\n", " ")
    time_text = " ".join(time_text.split())

    # append to Pandas DataFrame
    data.append({"title": title_text, "date": date_text, "time": time_text})
    # print(title_text + " " + supporting_acts_text + " " + date_text + " " + time_text)

df = pd.DataFrame(data)
print(df)