我以前做过一个小项目，用BeautifulSoup抓取一个真实的地产网站，但是抓取大约5,000个数据点花了很长时间。我想学习多线程处理，然后用BS实现它，但是有人告诉我，用Scrapy抓取网页可能更快更容易。另外，我已经从使用Spyder切换到Pycharm作为我的IDE。它仍然是不和谐的经验，但我正在努力适应它。
我已经看过一次文档，并遵循了一些使用Scrapy抓取的例子，但我仍然遇到困难。我计划使用我以前创建的BS抓取脚本作为基础，并创建一个新的Scrapy项目来网页抓取真实的地产数据。但是，我不知道如何以及从哪里开始。任何和所有的帮助都非常感谢。谢谢。

**想要的结果：**使用Scrapy从多个URL抓取多个页面。输入公寓清单链接并从每个链接取得数据，即可抓取多个值。
Scrapy脚本（目前为止）：

# -*- coding: utf-8 -*-

# Import library

import scrapy

# Create Spider class

class UneguiApartmentSpider(scrapy.Spider):
    name = 'apartments'
    allowed_domains = ['www.unegui.mn']
    start_urls = [
        'https://www.unegui.mn/l-hdlh/l-hdlh-zarna/oron-suuts-zarna/'
        ]
    # headers
    headers = {
        "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36"
    }

    def parse(self, response):
        for listings in response.xpath("//div[@class='list-announcement']"):
            item = ApartmentsItem()
            item['name'] = listings.xpath('text()').extract()
            item['link'] = listings.xpath('href').extract()
        yield item

靓汤剧本：

这个脚本仍然有一些问题，我试图解决，如刮城市和价格。例如，为4卧室公寓url（/4-r/），它创建一个错误或空值，因为有VIP列表

# -*- coding: utf-8 -*-

import requests
from bs4 import BeautifulSoup as BS
from datetime import datetime, timedelta
from dateutil.relativedelta import relativedelta
from timeit import default_timer as timer
import pandas as pd
import re
import csv

dt_today = datetime.today()
date_today = dt_today.strftime('%Y-%m-%d')
date_today2 = dt_today.strftime('%Y%m%d')
date_yesterday = (dt_today-relativedelta(day=1)).strftime('%Y-%m-%d')

def main():
    page = 0
    name = []
    date = []
    address = []
    district = []
    city = []
    price = []
    area_sqm = []
    rooms = []
    floor = []
    commission_year = []
    building_floors = []
    garage = []
    balcony = []
    windows = []
    window_type = []
    floor_type = []
    door_type = []
    leasing = []
    description = []
    link = []

    for i in range (5,6):
        BASE = 'https://www.unegui.mn'
        URL = f'{BASE}/l-hdlh/l-hdlh-zarna/oron-suuts-zarna/{i}-r/?page='
        COLUMNS=['Name','Date','Address','District','City','Price','Area_sqm','Rooms','Floor','Commission_year',
                 'Building_floors','Garage', 'Balcony','Windows','Window_type','Floor_type','door_type','Leasing','Description','Link']

        with requests.Session() as session:
            while True:
                (r := session.get(f'{URL}{page+1}')).raise_for_status()
                m = re.search('.*page=(\d+)$', r.url)
                if m and int(m.group(1)) == page:
                    break
                page += 1
                start = timer()
                print(f'Scraping {i} bedroom apartments page {page}')

                soup = BS(r.text, 'lxml')
                for tag in soup.findAll('div', class_='list-announcement-block'):
                    _name = tag.find('a', attrs={'itemprop': 'name'})
                    name.append(_name.get('content', 'N/A'))
                    if (_link := _name.get('href', None)):
                        link.append(f'{BASE}{_link}')
                        (_r := session.get(link[-1])).raise_for_status()
                        _spanlist = BS(_r.text, 'lxml').find_all('span', class_='value-chars')
                        floor_type.append(_spanlist[0].get_text().strip())
                        balcony.append(_spanlist[1].get_text().strip())
                        garage.append(_spanlist[2].get_text().strip())
                        window_type.append(_spanlist[3].get_text().strip())
                        door_type.append(_spanlist[4].get_text().strip())   
                        windows.append(_spanlist[5].get_text().strip())

                        _alist = BS(_r.text, 'lxml').find_all('a', class_='value-chars')
                        commission_year.append(_alist[0].get_text().strip())
                        building_floors.append(_alist[1].get_text().strip())
                        area_sqm.append(_alist[2].get_text().strip())
                        floor.append(_alist[3].get_text().strip())
                        leasing.append(_alist[4].get_text().strip())
                        district.append(_alist[5].get_text().strip())
                        address.append(_alist[6].get_text().strip())

                        rooms.append(tag.find('div', attrs={'announcement-block__breadcrumbs'}).get_text().split('»')[1].strip())
                        description.append(tag.find('div', class_='announcement-block__description').get_text().strip())
                        date.append(tag.find('div', class_='announcement-block__date').get_text().split(',')[0].strip())
                        city.append(tag.find('div', class_='announcement-block__date').get_text().split(',')[1].strip())         
                        # if ( _price := tag.find('div', class_='announcement-block__price _premium')) is None:
                        #     _price = tag.find('meta', attrs={'itemprop': 'price'})['content']

                        # price.append(_price)
                        end = timer()
                print(timedelta(seconds=end-start))

            df = pd.DataFrame(zip(name, date, address, district, city, 
                                  price, area_sqm, rooms, floor, commission_year,
                                  building_floors, garage, balcony, windows, window_type,
                                  floor_type, door_type, leasing, description, link), columns=COLUMNS)
            return(df)

        df['Date'] = df['Date'].replace('Өнөөдөр', date_today)
        df['Date'] = df['Date'].replace('Өчигдөр', date_yesterday)
        df['Area_sqm'] = df['Area_sqm'].replace('м²', '')
        df['Balcony'] = df['Balcony'].replace('тагттай', '')

if __name__ == '__main__':
    df = main()
    df.to_csv(f'{date_today2}HPD.csv', index=False)