网页抓取无法同时获取页面中所有链接的数据

Question

从某一天起，我试图从vesselfinder与其描述页面抓取所有船舶数据，如从描述页面我想要其信息，如船舶类型，Imo编号等表格形式。我尝试了不同的方法，但仍然有很多错误。首先，我发现我如何通过这些链接到它的描述页面，如何从所有页面获得所有这些链接，以及如何从它的描述页面获得特定的表数据(这仍然不完整，但得到一些)。但是今天我试图同时从所有链接的描述页面中获取数据，它给了我很多错误，这让我很困惑(通过组合代码)。我附加了我的代码，这是不好的，但到目前为止，#print(len(vessellist))它工作之后…错误…

import requests
from bs4 import BeautifulSoup
import pandas as pd
headers = {
'user-agent': 'Mozilla/5.0',
'accept-language': 'en-GB,en-US;q=0.9,en;q=0.8',
}
baseurl = 'https://www.vesselfinder.com/vessels'
vessellist = []
for x in range(1,6):
response = requests.get(
f'https://www.vesselfinder.com/vessels?page={x}', 
headers=headers)
soup = BeautifulSoup(response.content, 'html.parser')
contents = soup.find_all('td', class_='v2')
for property in contents:
for item in property.find_all('a', href=True):
vessellist.append(baseurl + item['href'])

for link in vessellist:
response = requests.get(link, headers=headers)
soup = BeautifulSoup(response.content, 'html.parser')
table = soup.find('table', class_ = 'tparams')
head = []
for i in table.find_all('td', class_ = 'n3'):
title = i.text
head.append(title)
values =[]
for row in table.find_all('td', class_ = 'v3'):
data = row.text
values.append(data)
df = pd.DataFrame(values)
print(df)

Answer 1

两步:获取汇总数据(包括href)。接下来是详细的。论文两个步骤实现在两个函数。这里我得到了前10页，有200页可用。

import requests as rq
from bs4 import BeautifulSoup as bs
from requests.api import head
headers = {"User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:78.0) Gecko/20100101 Firefox/78.0"}

def getSummaryData():
data = []
url = "https://www.vesselfinder.com/vessels"
for page in range(1, 10+1, 1): # only 200 first pages autorized ?
print("Page : %d/10" % page)
resp = rq.get(url + "?page=%s" % page, headers=headers)
soup = bs(resp.content, "lxml")
section = soup.find_all('section', {'class', 'listing'})[0]
tbody = section.find_all('tbody')[0]
trs = tbody.find_all('tr')
for tr in trs:
tds = tr.find_all('td')
# column 1 data
sub = tds[1].find('a')
href = sub['href']
divs = sub.find_all('div')
country = divs[0]['title']
sub_divs = divs[1].find_all('div')
vessel_name = sub_divs[0].text
vessel_type = sub_divs[1].text
# column 2 data
build_year = tds[2].text
# column 3 data
gt = tds[3].text
# column 4 data
dwt = tds[4].text
# column 5 data
size = tds[5].text
# save data
tr_data = {'country': country, 
'vessel_name': vessel_name,
'vessel_type': vessel_type,
'build_year': build_year,
'gt': gt,
'dwt': dwt,
'size': size,
'href': href}
data.append(tr_data)
return data
def getDetailledData(data):
for (iel, el) in enumerate(data):
print("%d/%d" % (iel+1, len(data)))
url = "https://www.vesselfinder.com" + el['href']
# make get call
resp = rq.get(url, headers=headers)
soup = bs(resp.content, "lxml")

# position and voyage data
table = soup.find_all('table', {'class', 'aparams'})[0]
trs = table.find_all('tr')
labels = ["course_speed", "current_draught","navigation_status",
"position_received", "IMO_MMSI", "callsign", "flag", "length_beam"]
for (i, tr) in enumerate(trs):
td = tr.find_all('td')[1]
el.update({'%s' % labels[i]: td.text})
# vessel particulars
table = soup.find_all('table', {'class', 'tparams'})[0]
trs = table.find_all('tr')
labels = ["IMO_number", "vessel_name", "ship_type", "flag", 
"homeport", "gross_tonnage", "summer_deadweight_t", 
"length_overall_m", "beam_m", "draught_m", "year_of_built", 
"builder", "place_of_built", "yard", "TEU", "crude", "grain", 
"bale", "classification_society", "registered_owner", "manager"]
for (i, tr) in enumerate(trs):
td = tr.find_all('td')[1]
el.update({'%s' % labels[i]: td.text})
#break
return data

调用函数:

data = getSummaryData() # href include
data = getDetailledData(data)

不要依赖'class'标签来定位数据。通常，您需要遍历table ->然后进行TDS或TRS检查以确保正确。