时间戳

首页 > 解决方案 > 在 IBM Watson Studio Jupyter Notebook 中使用 BeautifulSoup 进行 Web 抓取不起作用

html - 在 IBM Watson Studio Jupyter Notebook 中使用 BeautifulSoup 进行 Web 抓取不起作用

问题描述

我希望从此搜索结果页面中抓取 IBM Watson Studio Jupyter Notebook 中的数据：

https://www.aspc.co.uk/search/?PrimaryPropertyType=Rent&SortBy=PublishedDesc&LastUpdated=AddedAnytime&SearchTerm=&PropertyType=Residential&PriceMin=&PriceMax=&Bathrooms=&OrMoreBathrooms=true&Bedrooms=&OrMoreBedrooms=true&HasCentralHeating=false&HasGarage=false&HasDoubleGarage=false&HasGarden=false&IsNewBuild=false&IsDevelopment=false&IsParkingAvailable=false&IsPartExchangeConsidered=false&PublicRooms=&OrMorePublicRooms=true&IsHmoLicense=false&IsAllowPets=false&IsAllowSmoking=false&IsFullyFurnished=false&IsPartFurnished=false&IsUnfurnished=false&ExcludeUnderOffer=false&IncludeClosedProperties=true&ClosedDatesSearch=14&MapSearchType=EDITED&ResultView=LIST&ResultMode=NONE&AreaZoom=13&AreaCenter[lat]=57.14955426557916&AreaCenter[lng]=-2.0927401123046785&EditedZoom=13&EditedCenter[lat]=57.14955426557916&EditedCenter[lng]=-2.0927401123046785

我已经尝试过 BeautifulSoup 并尝试过 Selenium（完全披露：我是初学者）对多种代码变体。我已经解决了关于 Stack Overflow、Medium 文章等的几十个问题，但我无法理解我做错了什么。

我正在做的最新一个是：

from bs4 import BeautifulSoup
html_soup = BeautifulSoup(response.text, 'html.parser')
type(html_soup)

properties_containers = html_soup.find_all('div', class_ = 'information-card property-card  col  ')
print(type(properties_containers))
print(len(properties_containers))

这将返回 0。

<class 'bs4.element.ResultSet'>
0

有人可以指导我正确的方向吗？我做错了什么/错过了什么？

标签： htmlweb-scrapingbeautifulsoupjupyter-notebookibm-watson

解决方案

您看到的数据是通过 JavaScript 加载的。BeautifulSoup 无法执行它，但您可以使用requests模块从其 API 加载数据。

例如：

import json
import requests


url = 'https://www.aspc.co.uk/search/?PrimaryPropertyType=Rent&SortBy=PublishedDesc&LastUpdated=AddedAnytime&SearchTerm=&PropertyType=Residential&PriceMin=&PriceMax=&Bathrooms=&OrMoreBathrooms=true&Bedrooms=&OrMoreBedrooms=true&HasCentralHeating=false&HasGarage=false&HasDoubleGarage=false&HasGarden=false&IsNewBuild=false&IsDevelopment=false&IsParkingAvailable=false&IsPartExchangeConsidered=false&PublicRooms=&OrMorePublicRooms=true&IsHmoLicense=false&IsAllowPets=false&IsAllowSmoking=false&IsFullyFurnished=false&IsPartFurnished=false&IsUnfurnished=false&ExcludeUnderOffer=false&IncludeClosedProperties=true&ClosedDatesSearch=14&MapSearchType=EDITED&ResultView=LIST&ResultMode=NONE&AreaZoom=13&AreaCenter[lat]=57.14955426557916&AreaCenter[lng]=-2.0927401123046785&EditedZoom=13&EditedCenter[lat]=57.14955426557916&EditedCenter[lng]=-2.0927401123046785'
api_url = 'https://api.aspc.co.uk/Property/GetProperties?{}&Sort=PublishedDesc&Page=1&PageSize=12'

params = url.split('?')[-1]
data = requests.get(api_url.format(params)).json()

# uncomment this to print all data:
# print(json.dumps(data, indent=4))                     # <-- uncomment this to see all data received from server

# print some data to screen:
for property_ in data:
    print(property_['Location']['AddressLine1'])
    print(property_['CategorisationDescription'])
    print('Bedrooms:', property_["Bedrooms"])           # <-- print number of Bedrooms
    print('Bathrooms:', property_["Bathrooms"])         # <-- print number of Bathrooms
    print('PublicRooms:', property_["PublicRooms"])     # <-- print number of PublicRooms
    # .. etc.
    print('-' * 80)

印刷：

44 Roslin Place
Fully furnished 2 Bdrm 1st flr Flat. Hall. Lounge. Dining kitch. 2 Bdrms. Bathrm (CT band - C). Deposit 1 months rent. Parking. No pets. No smokers. Rent £550 p.m Entry by arr. Viewing contact solicitors. Landlord reg: 871287/100/26061. (EPC band - B).
Bedrooms: 2
Bathrooms: 1
PublicRooms: 1
--------------------------------------------------------------------------------
Second Floor Left,  173 Victoria Road
Unfurnished 1 Bdrm 2nd flr Flat. Hall. Lounge. Dining kitch. Bdrm. Bathrm (CT Band - A). Deposit 1 months rent. No pets. No smokers. Rent £375 p.m Immed entry. Viewing contact solicitors. Landlord reg: 1261711/100/09072. (EPC band - D).
Bedrooms: 1
Bathrooms: 1
PublicRooms: 1
--------------------------------------------------------------------------------
102 Bedford Road
Fully furnished 3 Bdrm 1st flr Flat. Hall. Lounge. Kitch. 3 Bdrms. Bathrm (CT band - B). Deposit 1 months rent. Garden. HMO License. No pets. No smokers. Rent £750 p.m Entry by arr. Viewing contact solicitors. Landlord reg: 49171/100/27130. (EPC band - D).
Bedrooms: 3
Bathrooms: 1
PublicRooms: 1
--------------------------------------------------------------------------------

... and so on.

推荐阅读