recently started getting into web scraping and i have managed ok but now im stuck and i cant find the answer or figure it out.
Here is my code for scraping and exporting info from a single page
import requests
page = requests.get("https://www.example.com/page.aspx?sign=1")
from bs4 import BeautifulSoup
soup = BeautifulSoup(page.content, 'html.parser')
#finds the right heading to grab
box = soup.find('h1').text
heading = box.split()[0]
#finds the right paragraph to grab
reading = soup.find_all('p')[0].text
print (heading, reading)
import csv
from datetime import datetime
# open a csv file with append, so old data will not be erased
with open('index.csv', 'a') as csv_file:
writer = csv.writer(csv_file)
writer.writerow([heading, reading, datetime.now()])
Problem occurs when i try to scrape multiple pages at the same time.
They are all the same just pagination changes eg
https://www.example.com/page.aspx?sign=1
https://www.example.com/page.aspx?sign=2
https://www.example.com/page.aspx?sign=3
https://www.example.com/page.aspx?sign=4 etc
Instead of writing the same code 20 times how do i stick all the data in a tuple or an array and export to csv.
Many thanks in advance.
Just try it out with a loop, until you got no page available (request is not OK). Should be easy to get.
import requests
from bs4 import BeautifulSoup
import csv
from datetime import datetime
results = []
page_number = 1
while True:
response = requests.get(f"https://www.example.com/page.aspx?sign={page_number}")
if response.status_code != 200:
break
soup = BeautifulSoup(page.content, 'html.parser')
#finds the right heading to grab
box = soup.find('h1').text
heading = box.split()[0]
#finds the right paragraph to grab
reading = soup.find_all('p')[0].text
# write a list
# results.append([heading, reading, datetime.now()])
# or tuple.. your call
results.append((heading, reading, datetime.now()))
page_number = page_number + 1
with open('index.csv', 'a') as csv_file:
writer = csv.writer(csv_file)
for result in results:
writer.writerow(result)
Related
I need to loop all the entries of all the pages from this link, then click the menu check in the red part (please see the image below) to enter the detail of each entry:
The objective is to cralwer the infos from the pages such as image below, and save left part as column names and right part as rows:
The code I used:
import requests
import json
import pandas as pd
import numpy as np
from bs4 import BeautifulSoup
url = 'http://bjjs.zjw.beijing.gov.cn/eportal/ui?pageId=425000'
content = requests.get(url).text
soup = BeautifulSoup(content, 'lxml')
table = soup.find('table', {'class': 'gridview'})
df = pd.read_html(str(table))[0]
print(df.head(5))
Out:
序号 工程名称 ... 发证日期 详细信息
0 NaN 假日万恒社区卫生服务站装饰装修工程 ... 2020-07-07 查看
The code for entering the detailed pages:
url = 'http://bjjs.zjw.beijing.gov.cn/eportal/ui?pageId=308891&t=toDetail&GCBM=202006202001'
content = requests.get(url).text
soup = BeautifulSoup(content, 'lxml')
table = soup.find("table", attrs={"class":"detailview"}).findAll("tr")
for elements in table:
inner_elements = elements.findAll("td", attrs={"class":"label"})
for text_for_elements in inner_elements:
print(text_for_elements.text)
Out:
工程名称:
施工许可证号:
所在区县:
建设单位:
工程规模(平方米):
发证日期:
建设地址:
施工单位:
监理单位:
设计单位:
行政相对人代码:
法定代表人姓名:
许可机关:
As you can see, I only get column name, no entries have been successfully extracted.
In order to loop all pages, I think we need to use post requests, but I don't know how to get headers.
Thanks for your help at advance.
This script will go for all pages and gets the data into a DataFrame and saves them to data.csv.
(!!! Warning !!! there are 2405 pages total, so it takes a long time to get them all):
import requests
import pandas as pd
from pprint import pprint
from bs4 import BeautifulSoup
url = 'http://bjjs.zjw.beijing.gov.cn/eportal/ui?pageId=425000'
payload = {'currentPage': 1, 'pageSize':15}
def scrape_page(url):
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
return {td.get_text(strip=True).replace(':', ''): td.find_next('td').get_text(strip=True) for td in soup.select('td.label')}
all_data = []
current_page = 1
while True:
print('Page {}...'.format(current_page))
payload['currentPage'] = current_page
soup = BeautifulSoup(requests.post(url, data=payload).content, 'html.parser')
for a in soup.select('a:contains("查看")'):
u = 'http://bjjs.zjw.beijing.gov.cn' + a['href']
d = scrape_page(u)
all_data.append(d)
pprint(d)
page_next = soup.select_one('a:contains("下一页")[onclick]')
if not page_next:
break
current_page += 1
df = pd.DataFrame(all_data)
df.to_csv('data.csv')
Prints the data to screen and saves data.csv (screenshot from LibreOffice):
I have tried reading a table from a website. It can be seen from my code that I have gone too far to get the table, I would appreciate if someone give me an opportunity to learn a quick method to do the same.
Here's my code:
import urllib.request
from bs4 import BeautifulSoup
url = "http://www.kazusa.or.jp/codon/cgi-bin/showcodon.cgi?species=9606&aa=1&style=N"
html = urllib.request.urlopen(url).read()
soup = BeautifulSoup(html)
text = soup.get_text()
with open('myfile.txt', 'w') as file:
file.writelines(text)
with open('myfile.txt','r') as g:
f = g.readlines()
tab = f[12:31]
table = [x.strip() for x in tab]
Every time running the code messes up with writing and reading the file.
You shouldn't need files. Filter for the pre tag instead, to target the table alone.
soup = BeautifulSoup(html)
text=soup.find('pre')
table = [x.strip() for x in text]
I have written below code to get the data from the website in CSV.
Basically I am interested in text like this in entirety.
(Beskrivning:
PL-CH-DSPTC-AD10Semi-professional Technician / Administrator: Vocationally trained positions that need both practical and theoretical understanding and some significant advanced vocational experience to perform broad range of varying tasks and issues, in related field of work. Work performed is still procedurized, however issues and problems)
So My table should have one row for each description please
from bs4 import BeautifulSoup
import requests
import pandas as pd
import csv
url = "http://www.altrankarlstad.com/wisp"
page = requests.get(url)
pagetext = page.text
soup = BeautifulSoup(pagetext, 'html.parser')
gdp_table = soup.find("table", attrs={"class": "table workitems-table mt-2"})
def table_to_df(table):
return pd.DataFrame([[td.text for td in row.findAll('td')] for row in table.tbody.findAll('tr')])
file = open("data.csv", 'w')
for row in soup.find_all('tr'):
for col in row.find_all('td'):
print(col.text)
I'm performing the same web scraping pattern that I just learned from post , however, I'm unable to scrap the using below script. I keep getting an empty return and I know the tags are there. I want to find_all "mubox" then pulls values for O/U and goalie information. This so weird, what am I missing?
from bs4 import BeautifulSoup
import requests
import pandas as pd
page_link = 'https://www.thespread.com/nhl-scores-matchups'
page_response = requests.get(page_link, timeout=10)
# here, we fetch the content from the url, using the requests library
page_content = BeautifulSoup(page_response.content, "html.parser")
# Take out the <div> of name and get its value
tables = page_content.find_all("div", class_="mubox")
print (tables)
# Iterate through rows
rows = []
This site uses an internal API before rendering the data. This api is an xml file, you can get here which contains all the match information. You can parse it using beautiful soup :
from bs4 import BeautifulSoup
import requests
page_link = 'https://www.thespread.com/matchups/NHL/matchup-list_20181030.xml'
page_response = requests.get(page_link, timeout=10)
body = BeautifulSoup(page_response.content, "lxml")
data = [
(
t.find("road").text,
t.find("roadgoalie").text,
t.find("home").text,
t.find("homegoalie").text,
float(t.find("ot").text),
float(t.find("otmoney").text),
float(t.find("ft").text),
float(t.find("ftmoney").text)
)
for t in body.find_all('event')
]
print(data)
I have working code that scrapes a single Craigslist page for specific information, but what would I need to add in order to grab the data from ALL of the pages (not knowing how many pages ahead of time)?
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
my_url="https://portland.craigslist.org/search/sss?query=electronics&sort=date"
uClient=uReq(my_url) #sends GET request to URL
page_html=uClient.read() #reads returned data and puts it in a variable
uClient.close() #close the connection
#create a file that we will want later to write parsed data to
filename="ScrapedData.csv"
f=open(filename, 'w')
headers="date, location, title, price\n"
f.write(headers)
#use BS to parse the webpage
page_soup=soup(page_html,'html.parser') #applying BS to the obtained html
containers=page_soup.findAll('p',{'class','result-info'})
for container in containers:
container_date=container.findAll('time',{'class','result-date'})
date=container_date[0].text
try:
container_location=container.findAll('span',{'class','result-hood'})
location=container_location[0].text
except:
try:
container_location=container.findAll('span',{'class','nearby'})
location=container_location[0].text
except:
location='NULL'
container_title=container.findAll('a',{'class','result-title'})
title=container_title[0].text
try:
container_price=container.findAll('span',{'class','result-price'})
price=container_price[0].text
except:
price='NULL'
#to print to screen
print('date:'+date)
print('location:'+location)
print('title:'+title)
print('price:'+price)
#to write to csv
f.write(date+','+location.replace(",","-")+','+title.replace(","," ")+','+price+'\n')
f.close()
Apart from what sir Andersson has already shown, you can do that as well for this site:
import requests
from bs4 import BeautifulSoup
import csv
page_link = "https://portland.craigslist.org/search/sss?s={}&query=electronics&sort=date"
for link in [page_link.format(page) for page in range(0,1147,120)]: #this is the fix
res = requests.get(link)
soup = BeautifulSoup(res.text,'lxml')
for container in soup.select('.result-info'):
try:
date = container.select('.result-date')[0].text
except IndexError:
date = ""
try:
title = container.select('.result-title')[0].text
except IndexError:
title = ""
try:
price = container.select('.result-price')[0].text
except IndexError:
price = ""
print(date,title,price)
with open("craigs_item.csv","a",newline="",encoding="utf-8") as outfile:
writer = csv.writer(outfile)
writer.writerow([date,title,price])
You can try to loop through all pages by handling "s" parameter in URL until you find page with no results (page with text "search and you will find"):
import requests
results_counter = 0
while True:
my_url="https://portland.craigslist.org/search/sss?query=electronics&sort=date&s=%d" % results_counter
page_html = requests.get(my_url).text
if "search and you will find" in page_html:
break
else:
results_counter += 120
filename="ScrapedData.csv"
f=open(filename, 'w')
headers="date, location, title, price\n"
f.write(headers)
page_soup=soup(page_html,'html.parser') #applying BS to the obtained html
containers=page_soup.findAll('p',{'class','result-info'})
...