循环页面以便使用BeautifulSoup进行抓取

我的单页刮板：

import requests
import pandas as pd
from bs4 import BeautifulSoup

url = 'https://www.cvbankas.lt/?padalinys%5B0%5D=76&page=1'
soup = BeautifulSoup(requests.get(url).content, 'html.parser')

all_data = []
for h3 in soup.select('h3.list_h3'):
    job_title = h3.get_text(strip=True)
    company = h3.find_next(class_="heading_secondary").get_text(strip=True)
    salary = h3.find_next(class_="salary_amount").get_text(strip=True)
    location = h3.find_next(class_="list_city").get_text(strip=True)
    print('{:<50} {:<15} {:<15} {}'.format(company, salary, location, job_title))

    all_data.append({
        'Job Title': job_title,
        'Company': company,
        'Salary': salary,
        'Location': location
    })

df = pd.DataFrame(all_data)
df.to_csv('data.csv')

#tips = sns.load_dataset('data.csv')
#print(tips)

给我一个csv文件，但只有50行。我想抓取所有页面，本来想在HTML代码中查找，'class=':'prev_next'但是BACK和FORWARD相同，只是href不同。因此，我决定进行范围循环并更改页面：

import requests
import pandas as pd
from bs4 import BeautifulSoup

#url = 'https://www.cvbankas.lt/?padalinys%5B0%5D=76&page=1'
#soup = BeautifulSoup(requests.get(url).content, 'html.parser')
all_data = []
for i in range(1, 9):
    url = 'https://www.cvbankas.lt/?padalinys%5B0%5D=76&page='+str(i)
    print(url)
    soup = BeautifulSoup(requests.get(url).content, 'html.parser')
    for h3 in soup.select('h3.list_h3'):
        try:
            job_title = h3.get_text(strip=True)
            company = h3.find_next(class_="heading_secondary").get_text(strip=True)
            salary = h3.find_next(class_="salary_amount").get_text(strip=True)
            location = h3.find_next(class_="list_city").get_text(strip=True)
            print('{:<50} {:<15} {:<15} {}'.format(company, salary, location, job_title))
        except AttributeError:
            
            all_data.append({
                    'Job Title': job_title,
                    'Company': company,
                    'Salary': salary,
                    'Location': location
                })
        
df = pd.DataFrame(all_data)
df.to_csv('data.csv')

运行代码后，它仅保存5行，因此比我仅刮取一页的代码少10倍。

您将如何循环页面？页面从1到8

还有如何清理薪水对象？因为它是字符串，其中包含Nuo 2700或Iki 2500或具有两个数字，例如1000-3000。因为我想使用Salary列作为整数，所以我可以对Seaborn进行一些绘图。