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scraper.py
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scraper.py
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import pandas as pd
import numpy as np
df=pd.read_csv('/content/final.csv',header='infer')
!pip install selenium
import requests
from bs4 import BeautifulSoup
#datset label
n=int(input(" enter no webiste you want to check "))
for i in range(n):
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
driver = webdriver.tor()
driver.get("https://duckduckgo.com/.")
search_box = driver.find_element_by_name("q")
search_box.send_keys("python")
search_box = driver.find_element_by_name("q")
search_box.send_keys("python")
search_box.send_keys(Keys.RETURN)
search_results = driver.find_elements_by_css_selector("div.g")
urls = []
for result in search_results:
link = result.find_element_by_tag_name("p")
url = link.get("href")
urls.append(url)
response = requests.get(url)
html_content = response.content
# Use Beautiful Soup to parse the HTML content
soup = BeautifulSoup(html_content, "html.parser")
#we get the data with the beautifulsoup library
#after that we use nltp for arranging d text data in array seprated by comma
#the we compare the data from website to our data
#and if data matches it is under cyber crime
#hence proved
#problem is solved
#that website or blog is under cyber crime