Python Web Scrape Cycle选项卡
寻求帮助,以循环访问网站上的所有选项卡以捕获所有相关信息。Python Web Scrape Cycle选项卡
在以下站点中,有几个标签分别标记为5x5,5x10x5,10x10等。我不确定如何构造它,以便它会通过选项卡并在我的脚本中编写循环。感谢您的帮助。
下面是python脚本;
from urllib.request import urlopen as uReq from bs4 import BeautifulSoup as soup
import csv
urls = [
'https://www.lifestorage.com/storage-units/florida/orlando/32810/610-near-lockhart/?size=5x5'
]
filename = 'life_storage.csv'
f = open(filename, 'a+')
csv_writer = csv.writer(f)
headers = ['unit_size', 'unit_type', 'description', 'online_price', 'reg_price', 'store_address', 'store_city', 'store_state', 'store_postalcode' ]
##unit_size = 5'x10' withouth the '
##unit_type = climate controlled or not (this could be blank if non-climate)
##descirption = the level it's on and type of access.
##online_price = $##/mo text
##reg_price = the scratched off $## text
csv_writer.writerow(headers)
for my_url in urls:
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
page_soup = soup(page_html, 'html.parser')
store_locator = page_soup.findAll("div", {"itemprop": "address"})
containers = page_soup.findAll("ul", {"id": "spaceList"})
for container in containers:
for store_location in store_locator:
store_address1 = store_location.find("span", {"itemprop": "streetAddress"})
store_address = store_address1.text
store_city1 = store_location.find("span", {"itemprop": "addressLocality"})
store_city = store_city1.text
store_state1 = store_location.find("span", {"itemprop": "addressRegion"})
store_state = store_state1.text
store_postalcode1 = store_location.find("span", {"itemprop": "postalCode"})
store_postalcode = store_postalcode1.text
title_container = container.find("div", {"class": "storesRow"})
unit_size = title_container.text
unit_container = container.find("div", {"class": "storesRow"})
unit_type = unit_container.span.text
description_container = container.find("ul", {"class": "features"})
description = description_container.text
online_price_container = container.find("div", {"class": "priceBox"})
online_price = online_price_container.span.text
reg_price_container = container.find("div", {"class": "priceBox"})
reg_price = reg_price_container.i.text
csv_writer.writerow([unit_size, unit_type, description, online_price, reg_price, store_address, store_city, store_state, store_postalcode])
f.close()
下面是与循环相关的html正文的片段;
//////////\\\\\\\Description BOX <div class="storesRow">
<span>
<a href="/reservation/choose/?store=610&type=1"> 5' x 5'<sup>*</sup> - Climate Controlled </a>
</span>
<ul class="features">
<li>Indoor access</li>
<li>Ground Level</li>
</ul>
</div>
//////////\\\\\\\\\PRICE BOX
<div class="priceBox">
<span>
$25/mo
<i> $27</i>
</span>
<em class="pOnly ">Phone & online only</em>
<div class="specialsMessage">
</div>
</div>
//////////\\\\\\\\\ADDRESS BOX
<div itemprop="address" itemscope="" itemtype="https://schema.org/PostalAddress">
<em>
<i class="fa fa-map-marker"></i>
<span itemprop="streetAddress">7244 Overland Rd </span>
<span itemprop="addressLocality">Orlando</span>,
<span itemprop="addressRegion">FL</span>
<span itemprop="postalCode">32810</span>
</em>
</div>
电流输出
所需的输出
回答:
你错了凹痕 - writerow()
应该是内for
内。
但它可能需要更多工作才能从项目中挤出正确的文本。请参阅代码。
from urllib.request import urlopen as uReq from bs4 import BeautifulSoup as soup
import csv
urls = [
'https://www.lifestorage.com/storage-units/florida/orlando/32810/610-near-lockhart/?size=5x5'
]
filename = 'life_storage.csv'
f = open(filename, 'a+')
csv_writer = csv.writer(f)
headers = ['unit_size', 'unit_type', 'description', 'online_price', 'reg_price', 'store_address', 'store_city', 'store_state', 'store_postalcode' ]
##unit_size = 5'x10' withouth the '
##unit_type = climate controlled or not (this could be blank if non-climate)
##descirption = the level it's on and type of access.
##online_price = $##/mo text
##reg_price = the scratched off $## text
csv_writer.writerow(headers)
for my_url in urls:
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
page_soup = soup(page_html, 'html.parser')
store_location = page_soup.find("div", {"itemprop": "address"})
# need `li`
containers = page_soup.find("ul", {"id": "spaceList"}).findAll('li')
print('len(containers):', len(containers))
item = store_location.find("span", {"itemprop": "streetAddress"})
store_address = item.text.strip()
item = store_location.find("span", {"itemprop": "addressLocality"})
store_city = item.text.strip()
item = store_location.find("span", {"itemprop": "addressRegion"})
store_state = item.text.strip()
item = store_location.find("span", {"itemprop": "postalCode"})
store_postalcode = item.text.strip()
for container in containers:
item = container.find("div", {"class": "storesRow"})
if item and item.span:
text = item.span.text.strip()
parts = text.split('-')
if len(parts) > 0:
unit_size = parts[0].strip().replace('*', "")
else:
unit_size = ''
if len(parts) > 1:
unit_type = parts[1].strip()
else:
unit_type = ''
else:
continue
item = container.find("ul", {"class": "features"})
if item:
description = item.text.strip().replace("\n", ',')
else:
description = ''
item = container.find("div", {"class": "priceBox"})
if item and item.i:
reg_price = item.i.text.strip()
else:
reg_price = ''
if item and item.span:
if item.i:
item.i.extract() # remove <i>`
online_price = item.span.text.strip()
else:
online_price = ''
csv_writer.writerow([unit_size, unit_type, description, online_price, reg_price, store_address, store_city, store_state, store_postalcode])
f.close()
结果:
unit_size,unit_type,description,online_price,reg_price,store_address,store_city,store_state,store_postalcode 5' x 5',Climate Controlled,"Indoor access,Ground Level",$25/mo,$27,7244 Overland Rd,Orlando,FL,32810
5' x 5',,"Outdoor/Drive-up access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
5' x 10',,"Outdoor/Drive-up access,Ground Level",$46/mo,$50,7244 Overland Rd,Orlando,FL,32810
10' x 5',Climate Controlled,"Indoor access,Ground Level",$57/mo,$62,7244 Overland Rd,Orlando,FL,32810
5' x 10',Climate Controlled,"Indoor access,Ground Level",$67/mo,$73,7244 Overland Rd,Orlando,FL,32810
5' x 10',,"Outdoor/Drive-up access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
5' x 15',Climate Controlled,"Indoor access,Ground Level",$69/mo,$75,7244 Overland Rd,Orlando,FL,32810
10' x 10',,"Outdoor/Drive-up access,Ground Level",$105/mo,$115,7244 Overland Rd,Orlando,FL,32810
10' x 10',Climate Controlled,"Indoor access,Ground Level",$105/mo,$115,7244 Overland Rd,Orlando,FL,32810
10' x 10',Climate Controlled,"Indoor access,Ground Level",$124/mo,$136,7244 Overland Rd,Orlando,FL,32810
10' x 15',,"Outdoor/Drive-up access,Ground Level",$144/mo,$158,7244 Overland Rd,Orlando,FL,32810
10' x 16',,"Outdoor/Drive-up access,Ground Level",$145/mo,$159,7244 Overland Rd,Orlando,FL,32810
10' x 15',Climate Controlled,"Indoor access,Ground Level",$149/mo,$163,7244 Overland Rd,Orlando,FL,32810
10' x 18',,"Outdoor/Drive-up access,Ground Level",$149/mo,$163,7244 Overland Rd,Orlando,FL,32810
10' x 15',Climate Controlled,"Indoor access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
10' x 20',,"Outdoor/Drive-up access,Ground Level",$147/mo,$161,7244 Overland Rd,Orlando,FL,32810
10' x 25',Climate Controlled,"Indoor access,Ground Level",$175/mo,$192,7244 Overland Rd,Orlando,FL,32810
10' x 20',Climate Controlled,"Indoor access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
10' x 28',,"Outdoor/Drive-up access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
41' x 41',,"Outdoor/Drive-up access,Ground Level",$1400/mo,$1540,7244 Overland Rd,Orlando,FL,32810
22' x 25',,"Outdoor/Drive-up access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
18' x 38',,"Outdoor/Drive-up access,Ground Level",Check for Availability,,7244 Overland Rd,Orlando,FL,32810
以上是 Python Web Scrape Cycle选项卡 的全部内容, 来源链接: utcz.com/qa/266827.html