Веб-очистка Python, как зациклить все страницы/следующую страницу

Может кто-нибудь помочь мне, как зациклить следующую страницу, перепробовал все решения здесь, но, похоже, не может заставить его работать.

import pandas as pd
pd.options.mode.chained_assignment = None  # default='warn'  # to suppress "false positive" warnings
import datetime as dt
import requests
from bs4 import BeautifulSoup
import time



def getPage(url):
    attempt = 1
    while True:
        response = requests.get(url)
        if response.status_code == requests.codes.ok:
            return response.content
        else:
            time.sleep(0.5)
            attempt += 1
            if attempt > 3:
                print("Data could not be requested for url:  ", url, "  after  ", attempt, "  attempts")
                return None



if __name__ == '__main__':


    url = "https://www.opic.com/upphandlingar/"

    data_df = pd.DataFrame()  # all data from the websites is saved to this data frame
    # get data
    try:
        markup = getPage(url).decode('utf-8')
    except:
        markup = getPage(url)


    if markup is None:
        print("Nothing was found. Value of 'markup' is 'None'.")
        sys.exit()

    soup = BeautifulSoup(markup, 'lxml')

    containers = soup.findAll("a", {"class": "ListItem"})
    for container in containers:
        upplagtdatum = container.div.p.text.strip()
        titel = container.h3.text.strip()
        stad_kommun = container.span.text.strip()



        # ----------------------------------------------------------------------------------------------------------
        # Save data to data frame
        df = pd.DataFrame(data = {'Upplagtdatum': [upplagtdatum], 'Titel': [titel], 'Stad Kommun': [stad_kommun]})
        data_df = pd.concat([data_df, df], sort=False)


    #   SAVE DATA

    # Save data frame to csv-file

    filePathName = "data_" + dt.datetime.now().strftime('%Y-%m-%d') + ".csv"
    data_df.to_csv(filePathName, sep=';', index=False, encoding='utf-8')


    print(data_df)

import pandas as pd
pd.options.mode.chained_assignment = None  # default='warn'  # to suppress "false positive" warnings
import datetime as dt
import requests
from bs4 import BeautifulSoup
import time

def getPage(url):
    attempt = 1
    while True:
        response = requests.get(url)
        if response.status_code == requests.codes.ok:
            return response.content
        else:
            time.sleep(0.5)
            attempt += 1
            if attempt > 3:
                print("Data could not be requested for url:  ", url, "  after  ", attempt, "  attempts")
                return None

if __name__ == '__main__':

 url = "https://www.opic.com/upphandlingar/"

    data_df = pd.DataFrame()  # all data from the websites is saved to this data frame
    # get data
    try:
        markup = getPage(url).decode('utf-8')
    except:
        markup = getPage(url)


    if markup is None:
        print("Nothing was found. Value of 'markup' is 'None'.")
        sys.exit()

    soup = BeautifulSoup(markup, 'lxml')

    containers = soup.findAll("a", {"class": "ListItem"})
    for container in containers:
        upplagtdatum = container.div.p.text.strip()
        titel = container.h3.text.strip()
        stad_kommun = container.span.text.strip()

 # Save data to data frame
        df = pd.DataFrame(data = {'Upplagtdatum': [upplagtdatum], 'Titel': [titel], 'Stad Kommun': [stad_kommun]})
        data_df = pd.concat([data_df, df], sort=False)

filePathName = "data_" + dt.datetime.now().strftime('%Y-%m-%d') + ".csv"
    data_df.to_csv(filePathName, sep=';', index=False, encoding='utf-8')


    print(data_df)