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beautifulsoup to retrieve the date


beautifulsoup to retrieve the date

By : user2956197
Date : November 22 2020, 10:54 AM
To fix the issue you can do You can use find_all() to get all the meta tags with itemprop="datePublished":
code :
import urllib2
from bs4 import BeautifulSoup

url = 'http://www.homedepot.com/p/Husky-41-in-16-Drawer-Tool-Chest-and-Cabinet-Set-HOTC4016B1QES/205080371'
soup = BeautifulSoup(urllib2.urlopen(url=url))

print [meta.get('content') for meta in soup.find_all('meta', itemprop='datePublished')]
[
    '2014-11-27', 
    '2014-11-20', 
    '2014-12-15', 
    '2014-10-28', 
    '2014-10-10'
]
print [meta.get('content') for meta in soup.select('meta[itemprop="datePublished"]')]


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Retrieve location data using BeautifulSoup

Retrieve location data using BeautifulSoup


By : Ankit Goyal
Date : March 29 2020, 07:55 AM
around this issue I'd like to get the location information from the infobox on the following wiki.
code :
>>> table = soup.find("table", class_ = "infobox")
>>> name = table.find("th").text
>>> country = table.find("th",text="Country").parent.find("td").text
>>> table = soup.find("table", class_ = "infobox")
>>> name = table.find("th").text
>>> country = table.find("th",text="Country").parent.find("td").text
>>> country = table.find("th",text="Country").find_next_sibling().text #also works
>>> location =  table.find("th",text="Location").parent.find("td").text
>>> location = table.find("th",text="Location").find_next_sibling().text #also works
Beautifulsoup to retrieve the href list

Beautifulsoup to retrieve the href list


By : Kris
Date : November 22 2020, 10:48 AM
this will help You don't need to load the content of each found tag with BeautifulSoup over and over again.
Use CSS selectors to get all product links (a tag under a div with class="product-image")
code :
import urllib2
from bs4 import BeautifulSoup

url = 'http://www.homedepot.com/b/Husky/N-5yc1vZrd/Ntk-All/Ntt-chest%2Band%2Bcabinet?Ntx=mode+matchall&NCNI-5'
soup = BeautifulSoup(urllib2.urlopen(url))

for link in soup.select('div.product-image > a:nth-of-type(1)'):
    print link.get('href')
http://www.homedepot.com/p/Husky-41-in-16-Drawer-Tool-Chest-and-Cabinet-Set-HOTC4016B1QES/205080371
http://www.homedepot.com/p/Husky-26-in-6-Drawer-Chest-and-Cabinet-Combo-Black-C-296BF16/203420937
http://www.homedepot.com/p/Husky-52-in-18-Drawer-Tool-Chest-and-Cabinet-Set-Black-HOTC5218B1QES/204825971
http://www.homedepot.com/p/Husky-26-in-4-Drawer-All-Black-Tool-Cabinet-H4TR2R/204648170
...
links = [link.get('href') for link in soup.select('div.product-image > a:nth-of-type(1)')]
How to retrieve <th><td> using Beautifulsoup

How to retrieve <th><td> using Beautifulsoup


By : kete
Date : March 29 2020, 07:55 AM
I wish did fix the issue. The data is dynamically generated but you can mimic an ajax request and get it in json format:
code :
import requests

params = {"Code": "E00939",
          "PkgType": "11036",
          "val": "50"}
js = requests.get("http://data.tsci.com.cn/RDS.aspx", params=params).json()

print(js)
{u'BrokerBuy': [{u'AV': u'5.24',
                 u'BrokerNo': u'Optiver',
                 u'percent': u'10.09',
                 u'shares': u'43.06M',
                 u'turnover': u'225.67M'},
                {u'AV': u'5.26',
                 u'BrokerNo': u'UBS HK',
                 u'percent': u'4.81',
                 u'shares': u'20.47M',
                 u'turnover': u'107.63M'},
                {u'AV': u'5.22',
                 u'BrokerNo': u'\u4e2d\u94f6\u56fd\u9645',
                 u'percent': u'4.63',
                 u'shares': u'19.83M',
                 u'turnover': u'103.51M'},
                {u'AV': u'5.25',
                 u'BrokerNo': u'\u745e\u4fe1',
                 u'percent': u'3.88',
                 u'shares': u'16.54M',
                 u'turnover': u'86.82M'},
                {u'AV': u'5.24',
                 u'BrokerNo': u'IMC',
                 u'percent': u'3.84',
                 u'shares': u'16.38M',
                 u'turnover': u'85.89M'}],
 u'BrokerSell': [{u'AV': u'5.21',
                  u'BrokerNo': u'\u4e2d\u6295\u4fe1\u606f',
                  u'percent': u'8.90',
                  u'shares': u'38.19M',
                  u'turnover': u'199.12M'},
                 {u'AV': u'5.24',
                  u'BrokerNo': u'Optiver',
                  u'percent': u'5.51',
                  u'shares': u'23.55M',
                  u'turnover': u'123.29M'},
                 {u'AV': u'5.24',
                  u'BrokerNo': u'\u9ad8\u76db\u4e9a\u6d32',
                  u'percent': u'4.43',
                  u'shares': u'18.91M',
                  u'turnover': u'99.19M'},
                 {u'AV': u'5.28',
                  u'BrokerNo': u'JPMorgan',
                  u'percent': u'2.28',
                  u'shares': u'9.67M',
                  u'turnover': u'51.09M'},
                 {u'AV': u'5.25',
                  u'BrokerNo': u'IMC',
                  u'percent': u'0.88',
                  u'shares': u'3.76M',
                  u'turnover': u'19.70M'}],
 u'Buy': [{u'AV': u'5.24',
           u'BrokerNo': u'1499.Optiver',
           u'percent': u'10.09',
           u'shares': u'43.06M',
           u'turnover': u'225.67M'},
          {u'AV': u'5.24',
           u'BrokerNo': u'1453.IMC',
           u'percent': u'3.84',
           u'shares': u'16.38M',
           u'turnover': u'85.89M'},
          {u'AV': u'5.24',
           u'BrokerNo': u'7387.\u82b1\u65d7\u73af\u7403',
           u'percent': u'3.08',
           u'shares': u'13.16M',
           u'turnover': u'68.97M'},
          {u'AV': u'5.23',
           u'BrokerNo': u'6698.\u76c8\u900f\u8bc1\u5238',
           u'percent': u'1.74',
           u'shares': u'7.43M',
           u'turnover': u'38.86M'},
          {u'AV': u'5.21',
           u'BrokerNo': u'1799.\u8000\u624d\u8bc1\u5238',
           u'percent': u'1.44',
           u'shares': u'6.18M',
           u'turnover': u'32.16M'}],
 u'NetBuy': [{u'AV': u'5.25',
              u'BrokerNo': u'1499.Optiver',
              u'percent': u'4.58',
              u'shares': u'19.51M',
              u'turnover': u'102.37M'},
             {u'AV': u'5.24',
              u'BrokerNo': u'1453.IMC',
              u'percent': u'2.96',
              u'shares': u'12.62M',
              u'turnover': u'66.19M'},
             {u'AV': u'5.24',
              u'BrokerNo': u'7387.\u82b1\u65d7\u73af\u7403',
              u'percent': u'2.81',
              u'shares': u'11.98M',
              u'turnover': u'62.78M'},
             {u'AV': u'5.23',
              u'BrokerNo': u'6698.\u76c8\u900f\u8bc1\u5238',
              u'percent': u'1.66',
              u'shares': u'7.12M',
              u'turnover': u'37.24M'},
             {u'AV': u'5.26',
              u'BrokerNo': u'9065.UBS HK',
              u'percent': u'1.39',
              u'shares': u'5.91M',
              u'turnover': u'31.11M'}],
 u'NetNameBuy': [{u'AV': u'5.26',
                  u'BrokerNo': u'UBS HK',
                  u'percent': u'4.58',
                  u'shares': u'19.49M',
                  u'turnover': u'102.44M'},
                 {u'AV': u'5.25',
                  u'BrokerNo': u'Optiver',
                  u'percent': u'4.58',
                  u'shares': u'19.51M',
                  u'turnover': u'102.37M'},
                 {u'AV': u'5.22',
                  u'BrokerNo': u'\u4e2d\u94f6\u56fd\u9645',
                  u'percent': u'4.28',
                  u'shares': u'18.37M',
                  u'turnover': u'95.84M'},
                 {u'AV': u'5.24',
                  u'BrokerNo': u'\u745e\u4fe1',
                  u'percent': u'3.16',
                  u'shares': u'13.49M',
                  u'turnover': u'70.68M'},
                 {u'AV': u'5.24',
                  u'BrokerNo': u'IMC',
                  u'percent': u'2.96',
                  u'shares': u'12.62M',
                  u'turnover': u'66.19M'}],
 u'NetNameSell': [{u'AV': u'5.29',
                   u'BrokerNo': u'\u5174\u4e1a\u91d1\u878d',
                   u'percent': u'0.37',
                   u'shares': u'1.58M',
                   u'turnover': u'8.36M'},
                  {u'AV': u'5.25',
                   u'BrokerNo': u'\u4e2d\u56fd\u91d1\u878d',
                   u'percent': u'0.16',
                   u'shares': u'696K',
                   u'turnover': u'3.65M'},
                  {u'AV': u'5.32',
                   u'BrokerNo': u'\u94f6\u6cb3\u56fd\u9645',
                   u'percent': u'0.16',
                   u'shares': u'671K',
                   u'turnover': u'3.57M'},
                  {u'AV': u'5.29',
                   u'BrokerNo': u'Penjing',
                   u'percent': u'0.07',
                   u'shares': u'300K',
                   u'turnover': u'1.59M'},
                  {u'AV': u'5.31',
                   u'BrokerNo': u'\u5efa\u94f6\u56fd\u9645',
                   u'percent': u'0.06',
                   u'shares': u'272K',
                   u'turnover': u'1.44M'}],
 u'NetSell': [{u'AV': u'5.21',
               u'BrokerNo': u'6999.\u4e2d\u6295\u4fe1\u606f',
               u'percent': u'8.61',
               u'shares': u'36.93M',
               u'turnover': u'192.59M'},
              {u'AV': u'5.24',
               u'BrokerNo': u'3440.\u9ad8\u76db\u4e9a\u6d32',
               u'percent': u'4.03',
               u'shares': u'17.20M',
               u'turnover': u'90.15M'},
              {u'AV': u'5.30',
               u'BrokerNo': u'5337.JPMorgan',
               u'percent': u'0.67',
               u'shares': u'2.83M',
               u'turnover': u'15.00M'},
              {u'AV': u'5.29',
               u'BrokerNo': u'5980.\u5174\u4e1a\u91d1\u878d',
               u'percent': u'0.37',
               u'shares': u'1.58M',
               u'turnover': u'8.36M'},
              {u'AV': u'5.30',
               u'BrokerNo': u'8738.\u6c47\u4e30\u8bc1\u5238',
               u'percent': u'0.36',
               u'shares': u'1.53M',
               u'turnover': u'8.10M'}],
 u'Sell': [{u'AV': u'5.21',
            u'BrokerNo': u'6999.\u4e2d\u6295\u4fe1\u606f',
            u'percent': u'8.90',
            u'shares': u'38.19M',
            u'turnover': u'199.12M'},
           {u'AV': u'5.24',
            u'BrokerNo': u'1499.Optiver',
            u'percent': u'5.51',
            u'shares': u'23.55M',
            u'turnover': u'123.29M'},
           {u'AV': u'5.24',
            u'BrokerNo': u'3440.\u9ad8\u76db\u4e9a\u6d32',
            u'percent': u'4.19',
            u'shares': u'17.89M',
            u'turnover': u'93.75M'},
           {u'AV': u'5.25',
            u'BrokerNo': u'1453.IMC',
            u'percent': u'0.88',
            u'shares': u'3.76M',
            u'turnover': u'19.70M'},
           {u'AV': u'5.30',
            u'BrokerNo': u'5337.JPMorgan',
            u'percent': u'0.70',
            u'shares': u'2.96M',
            u'turnover': u'15.66M'}],
 u'Total': {u'In': u'1.26B',
            u'Net': u'5.800971E+08',
            u'Out': u'682.58M',
            u'right': u'98.71'}}
for code in stock_code:
    params["Code"] = "E{}".format(code)
    js = requests.get("http://data.tsci.com.cn/RDS.aspx", params=params).json()
Cannot Retrieve contents of a page using BeautifulSoup

Cannot Retrieve contents of a page using BeautifulSoup


By : Ricky Zhang
Date : March 29 2020, 07:55 AM
hop of those help? The site may be configured to send different pages based on the User-Agent. I ran into the same problem as you did. It returned an empty list. Adding a generic user agent to the headers solved it for me.
code :
from bs4 import BeautifulSoup
import requests
root = 'https://www.quora.com/topic/Graduate-Record-Examination-GRE-1'
headers = {'User-Agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X x.y; rv:42.0) Gecko/20100101 Firefox/42.' }
r = requests.get(root,headers=headers)
soup = BeautifulSoup(r.text,'html.parser')
f = soup.findAll('div',{'class':'paged_list_wrapper'})
print(f)
How to input date range in html date-picker when scraping with beautifulsoup?

How to input date range in html date-picker when scraping with beautifulsoup?


By : Mohamed Gamal
Date : March 29 2020, 07:55 AM
this will help The following should help you click the calendar menu and input values using Selenium. There is an Ajax POST made by the page but I was unable to pass the right cookies (I think)
code :
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC

d = webdriver.Chrome()
d.get('https://www.investing.com/funds/lansforsakringar-global-indexnara-historical-data')
try:  #attempt to dismiss banners that could block later clicks
    WebDriverWait(d, 10).until(EC.element_to_be_clickable((By.CSS_SELECTOR, ".closer"))).click()
    d.find_element_by_css_selector('.closer').click()
except:
    pass
d.find_element_by_id('widgetFieldDateRange').click() #show the date picker
sDate  = d.find_element_by_id('startDate') # set start date input element into variable
sDate.clear() #clear existing entry
sDate.send_keys('01/18/2019') #add custom entry
eDate = d.find_element_by_id('endDate') #repeat for end date
eDate.clear()
eDate.send_keys('04/18/2019')
d.find_element_by_id('applyBtn').click() #submit changes
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