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Extract MCQ Questions of Specific topic from sanfoundry.com Web Scrapping
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bs4 | |
lxml | |
html5lib | |
pymongo | |
'pymongo[srv]' | |
dnspython |
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#!/usr/bin/env python3 | |
__author__ = "Ved Prakash Gupta" | |
__copyright__ = f"Copyright (C) 2021 {__author__}" | |
__license__ = "Public Domain" | |
__version__ = "1.0" | |
from bs4 import BeautifulSoup | |
import requests | |
import sys | |
if len(sys.argv) == 2: | |
url = sys.argv[1] | |
else: | |
url = input("Enter the Sanfoundry Site Name : ") | |
# url = "https://www.sanfoundry.com/operating-system-questions-answers-basics/" | |
req = requests.get(url) | |
soup = BeautifulSoup(req.text, "html.parser") | |
print(soup.title.string) | |
# sf-postw-category | |
divs = soup.find_all('div' , {"class": "sf-postw-category"}) | |
os_link = [] | |
dic = {} | |
for link in divs[0].find_all('a'): | |
os_link.append(link.get('href')) | |
dic[link.string] = link.get('href') | |
# Extract Data from Links | |
contain_pages = [] | |
for link in os_link: | |
req = requests.get(link) | |
soup = BeautifulSoup(req.text, "html.parser") | |
divs = soup.find_all('div' , {"class" : "entry-content"}) | |
contain_pages.append(divs[0]) | |
contain_mcq_div = set({}) | |
for x in contain_pages: | |
div_mcq = x.find_all('p') | |
for i in range(len(div_mcq)-1 , -1 , -1): | |
e = str(div_mcq[i]).split("</div>") | |
for ele in e: | |
contain_mcq_div.add(ele) | |
mcq = [] | |
for x in contain_mcq_div: | |
try : | |
vs = x.index("<span") | |
s = x[:vs] | |
i = x[x.index("<div"):] | |
i = i[i.index(">"):] | |
mcq.append(f"{s}\n{i}") | |
except: | |
pass | |
# Total tag | |
tags=["a","br","abbr","acronym","address","area","b","base","bdo","big","blockquote","body","br","button","caption","cite","code","col","colgroup","dd","del","dfn","div","dl","DOCTYPE","dt","em","fieldset","form","h1","h2","h3","h4","h5","h6","head","html","hr","i","img","input","ins","kbd","label","legend","li","link","map","meta","noscript","object","ol","optgroup","option","p","param","pre","q","samp","script","select","small","span","strong","style","sub","sup","table","tbody","td","textarea","tfoot","th","thead","title","tr","tt","ul","var"] | |
tag_list = [] | |
for t in tags: | |
t,t2,t3 = f"<{t}>" , f"</{t}>", f"<{t}/>" | |
tag_list.append(t) | |
tag_list.append(t2) | |
tag_list.append(t3) | |
# print(tag_list) | |
mc = set(mcq) | |
mcq2 = [] | |
for m in mc: | |
for x in tag_list: | |
try: | |
m = m.replace(x , "") | |
except: | |
pass | |
mcq2.append(m) | |
print(f"len is {len(mcq2)}") | |
# Mcq list | |
# print(mcq2) |
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class copyit: | |
def __init__(self , link): | |
"""Initialize Class by Sanfoundry link""" | |
self.url = link | |
from bs4 import BeautifulSoup | |
import requests | |
req = requests.get(self.url) | |
soup = BeautifulSoup(req.text, "html.parser") | |
self.title = soup.title.string | |
print(self.title) | |
# sf-postw-category | |
divs = soup.find_all('div' , {"class": "sf-postw-category"}) | |
os_link = [] | |
dic = {} | |
for link in divs[0].find_all('a'): | |
os_link.append(link.get('href')) | |
dic[link.string] = link.get('href') | |
# Extract Data from Links | |
contain_pages = [] | |
for link in os_link: | |
req = requests.get(link) | |
soup = BeautifulSoup(req.text, "html.parser") | |
divs = soup.find_all('div' , {"class" : "entry-content"}) | |
contain_pages.append(divs[0]) | |
contain_mcq_div = set({}) | |
for x in contain_pages: | |
div_mcq = x.find_all('p') | |
for i in range(len(div_mcq)-1 , -1 , -1): | |
e = str(div_mcq[i]).split("</div>") | |
for ele in e: | |
contain_mcq_div.add(ele) | |
mcq = [] | |
for x in contain_mcq_div: | |
try : | |
vs = x.index("<span") | |
s = x[:vs] | |
i = x[x.index("<div"):] | |
i = i[i.index(">"):] | |
mcq.append(f"{s}\n{i}") | |
except: | |
pass | |
# Total tag | |
tags=["a","br","abbr","acronym","address","area","b","base","bdo","big","blockquote","body","br","button","caption","cite","code","col","colgroup","dd","del","dfn","div","dl","DOCTYPE","dt","em","fieldset","form","h1","h2","h3","h4","h5","h6","head","html","hr","i","img","input","ins","kbd","label","legend","li","link","map","meta","noscript","object","ol","optgroup","option","p","param","pre","q","samp","script","select","small","span","strong","style","sub","sup","table","tbody","td","textarea","tfoot","th","thead","title","tr","tt","ul","var"] | |
tag_list = [] | |
for t in tags: | |
t,t2,t3 = f"<{t}>" , f"</{t}>", f"<{t}/>" | |
tag_list.append(t) | |
tag_list.append(t2) | |
tag_list.append(t3) | |
# print(tag_list) | |
mc = set(mcq) | |
mcq2 = [] | |
for m in mc: | |
for x in tag_list: | |
try: | |
m = m.replace(x , "") | |
except: | |
pass | |
mcq2.append(m) | |
self.mcq = mcq2 | |
i = 1 | |
self.mcqdict = {} | |
for e in self.mcq: | |
self.mcqdict[i] = e | |
i = i+1 | |
def copyright(self): | |
"""Copyright Information""" | |
__author__ = "Ved Prakash Gupta" | |
__copyright__ = f"Copyright (C) 2021 {__author__}" | |
__license__ = "Public Domain" | |
__version__ = "1.0" | |
def extract_list(self): | |
"""MCQ Data in the form of list""" | |
return self.mcq | |
def extract_dict(self): | |
"""MCQ Data in dict form serial wise""" | |
return self.mcqdict | |
def extract_str(self): | |
"""MCQ String""" | |
return "\n\n".join(self.mcq) | |
def extract_pdf(self): | |
"""Save MCQ pdf""" | |
mcq3 = "\n\n".join(self.mcq) | |
f = open("data.txt" , "w") | |
f.write(mcq3) | |
f.close() | |
from fpdf import FPDF | |
pdf = FPDF(format='letter') #pdf format | |
pdf.add_page() #create new page | |
pdf.set_font("Courier", size=9) # font and textsize | |
file1 = open("data.txt" , "r") | |
data = file1.readlines() | |
pdf.cell(200 , 10 , txt = str(f"{self.title}").encode('latin-1', 'replace').decode('latin-1') , ln = 1 , align="C") | |
lineNum = 4 | |
for line in data: | |
try : | |
pdf.cell(100 , 8 , txt = str(line).encode('latin-1', 'replace').decode('latin-1') , ln = lineNum , align="L") | |
lineNum = lineNum + 1 | |
except: | |
pass | |
try : | |
pdf.output(f"{self.title}.pdf") | |
except Exception as e: | |
print(e) | |
Inventory Valuation & Depreciation Accounting
Inventory Valuation & Depreciation Accounting
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