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Webscraping
1.
from bs4 import BeautifulSoup
html="<!DOCTYPE html> <html> <head> <title>Page
Title</title> </head> <body> <h3><b id='boldest'> Lionel
Messi</b></h3> <p> Salary: $ 100,000,000 </p> <h3> Christiano
Ronaldo</h3> <p> Salary: $ 150,000,000 </p> <h3> Neymar Junior</h3> <p>
Saraly: $ 85,000,000</p> </body> </html>"
soup = BeautifulSoup(html, 'html5lib')tag_object=soup.title
tag_object=soup.h3
tag_child = tag_object.b
parent_tag=tag_child.parent
sibling_1 = tag_object.next_sibling
tag_child.attr
tag_child.string
2.
from bs4 import BeautifulSoup
html = "<table> <tr> <td>Pizza Place</td> <td>Orders</td>
<td>Slices</td> </tr> <tr> <td>Domino Pizza</td>
<td>10</td> <td>100</td> </tr> <tr> <td>Pizza
hut</td> <td>12</td> <td>144</td> </tr> </table>"
table = BeautifulSoup(html, 'html5lib')
table_row = table.find_all(name='tr')[<tr> <td>Pizza Place</td> <td>Orders</td> <td>Slices</td> </tr>,
<tr> <td>Domino Pizza</td> <td>10</td> <td>100</td> </tr>,
<tr> <td>Pizza hut</td> <td>12</td> <td>144</td> </tr>]first_row = table_row[0]<tr> <td>Pizza Place</td> <td>Orders</td> <td>Slices</td> </tr>for i, row in enumerate(table_rows):
print("row", i)
cells=row.find_all("td")
for j, cell in enumerate(cells):
print("column", j, "cell", cell)
3.
import requests
from bs4 import BeautifulSoup
page = requests.get("http://EnterWebsiteURL...).text
# creates a BeautifulSoup object
soup = BeautifulSoup(page, "html.parser")
# pulls all instance of <a> tag
artists = soup.find_all('a')
# clears data of all tags
for artist in artists:
names = artist.contents[0]
fullLink = artist.get('hred')
print(names)
print(fullLink)728x90
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