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QUZ/scrape_cbtbank.py
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2026-06-27 02:21:09 +00:00
import os
import sys
import time
import json
import sqlite3
import re
import argparse
import hashlib
import requests
from bs4 import BeautifulSoup
from urllib.parse import quote, unquote, urlparse
def html_to_markdown(html_content):
if not html_content:
return ""
soup = BeautifulSoup(html_content, 'html.parser')
# Process paragraph tags
for p in soup.find_all('p'):
p.insert_after('\n\n')
# Process line breaks
for br in soup.find_all('br'):
br.replace_with('\n')
# Process list items
for li in soup.find_all('li'):
li.insert_before('- ')
li.insert_after('\n')
# Process bold text
for strong in soup.find_all(['strong', 'b']):
text = strong.get_text()
if text:
strong.replace_with(f"**{text}**")
# Process links
for a in soup.find_all('a'):
text = a.get_text()
href = a.get('href', '')
if text and href:
a.replace_with(f"[{text}]({href})")
text = soup.get_text()
# Clean up excess newlines
lines = [line.rstrip() for line in text.split('\n')]
cleaned_text = '\n'.join(lines)
while '\n\n\n' in cleaned_text:
cleaned_text = cleaned_text.replace('\n\n\n', '\n\n')
return cleaned_text.strip()
def get_image_filename(url):
ext = os.path.splitext(urlparse(url).path)[1]
if not ext or len(ext) > 5:
ext = ".png"
h = hashlib.md5(url.encode('utf-8')).hexdigest()
return f"cbtbank_{h}{ext}"
def download_and_save_image(image_url, target_dir, delay=1.0):
if not image_url:
return None
# If it is a relative URL, make it absolute
if image_url.startswith('/'):
image_url = f"https://cbtbank.kr{image_url}"
if not image_url.startswith('http'):
return image_url
try:
os.makedirs(target_dir, exist_ok=True)
filename = get_image_filename(image_url)
dest_path = os.path.join(target_dir, filename)
if os.path.exists(dest_path):
return f"/assets/{filename}"
time.sleep(delay)
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}
r = requests.get(image_url, headers=headers, timeout=15)
if r.status_code == 200:
with open(dest_path, "wb") as f:
f.write(r.content)
print(f" [Image] Downloaded image: {filename}")
return f"/assets/{filename}"
else:
print(f" [Image Warning] Failed to download: {image_url} (HTTP {r.status_code})")
except Exception as e:
print(f" [Image Error] Error downloading image: {e}")
return image_url
def get_existing_question_ids(conn):
cursor = conn.cursor()
cursor.execute("SELECT id FROM QuizQuestions WHERE source = 'cbtbank'")
return {row[0] for row in cursor.fetchall()}
def scrape_exam(exam_name, selected_rounds=None, overwrite=False, delay=1.0, db_file="qple_quiz.db", assets_dir="./frontend/public/assets"):
conn = sqlite3.connect(db_file)
# Ensure correct_answers column exists in QuizQuestions table
cursor = conn.cursor()
cursor.execute("PRAGMA table_info(QuizQuestions)")
columns = [col[1] for col in cursor.fetchall()]
if "correct_answers" not in columns:
cursor.execute("ALTER TABLE QuizQuestions ADD COLUMN correct_answers TEXT DEFAULT ''")
conn.commit()
print(">>> Database Migration: Added correct_answers column to QuizQuestions table.")
existing_ids = get_existing_question_ids(conn)
print(f"\n>>> Connecting to SQLite DB: {db_file}")
print(f">>> Target Exam: {exam_name}")
# 1. Fetch main exam list page to find rounds
url = f"https://cbtbank.kr/category/{quote(exam_name)}"
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}
print(f">>> Fetching list of exam rounds from: {url}")
r = requests.get(url, headers=headers, timeout=15)
r.encoding = 'utf-8'
if r.status_code != 200:
print(f"[Error] Failed to fetch exam page: HTTP {r.status_code}")
conn.close()
return
soup = BeautifulSoup(r.text, 'html.parser')
# Find all links pointing to /exam/...
rounds = []
for a in soup.find_all('a'):
href = a.get('href', '')
if href.startswith('/exam/'):
round_id = href.split('/')[-1]
round_name = a.get_text().strip()
rounds.append({
'id': round_id,
'name': round_name,
'href': href
})
# Filter duplicate rounds preserving order
seen = set()
unique_rounds = []
for rnd in rounds:
if rnd['id'] not in seen:
seen.add(rnd['id'])
unique_rounds.append(rnd)
print(f"Found {len(unique_rounds)} unique rounds on cbtbank.kr:")
for rnd in unique_rounds:
print(f" - {rnd['name']} (ID: {rnd['id']})")
if selected_rounds:
filtered_rounds = [rnd for rnd in unique_rounds if rnd['id'] in selected_rounds or rnd['name'] in selected_rounds]
print(f"\n>>> Filtered to {len(filtered_rounds)} selected rounds: {[rnd['name'] for rnd in filtered_rounds]}")
unique_rounds = filtered_rounds
# 2. Iterate and scrape each round page
for round_idx, rnd in enumerate(unique_rounds, 1):
round_id = rnd['id']
round_name = rnd['name']
round_url = f"https://cbtbank.kr/exam/{round_id}"
print("\n" + "="*50)
print(f"Scraping Round ({round_idx}/{len(unique_rounds)}): {round_name}")
print(f"URL: {round_url}")
print("="*50)
time.sleep(delay)
r = requests.get(round_url, headers=headers, timeout=15)
r.encoding = 'utf-8'
if r.status_code != 200:
print(f" [Error] Failed to fetch round page: HTTP {r.status_code}")
continue
round_soup = BeautifulSoup(r.text, 'html.parser')
exams_div = round_soup.find(class_='exams')
if not exams_div:
print(" [Error] Could not find the questions container (class='exams') on this page.")
continue
current_subject = "일반"
parsed_questions_count = 0
# Iterate over the direct children of div.exams
for child in exams_div.children:
if not child.name:
continue
cl = child.get('class', [])
cl_str = " ".join(cl)
# 1. Update current subject if we encounter exam-class-title
if 'exam-class-title' in cl:
subject_text = child.get_text().strip()
if ':' in subject_text:
current_subject = subject_text.split(':', 1)[1].strip()
else:
current_subject = subject_text.strip()
print(f"\n >>> Subject switched to: {current_subject}")
continue
# 2. Process question containers (exam-box) nested inside row text-dark
if 'text-dark' in cl:
boxes = child.find_all(class_='exam-box')
for box in boxes:
q_id = box.get('question-id')
if not q_id:
continue
import zlib
q_id_int = zlib.crc32(q_id.encode('utf-8')) & 0x7fffffff
print(f" Question ID: {q_id} (Int: {q_id_int}) ({current_subject})")
if q_id_int in existing_ids and not overwrite:
print(f" -> {q_id} (Int: {q_id_int}) already exists in DB. Skipping.")
continue
# Extract title tag
title_tag = box.find(class_='exam-title')
if not title_tag:
print(" [Warning] Could not find exam-title. Skipping.")
continue
# Get question image (if any) in box (excluding choices and replies)
q_img_url = None
all_imgs = box.find_all('img')
for img in all_imgs:
# Check that this image is not inside reply or choices
if img.find_parent(class_='reply') or img.find_parent(class_='question-choice'):
continue
src = img.get('src')
if src and not any(x in src for x in ['kakao.png', 'line.png', 'facebook.png', 'twitter.png', 'band.png']):
q_img_url = src
break
# Clean question text by extracting the span.exam-number (question index)
import copy
title_tag_copy = copy.copy(title_tag)
num_span = title_tag_copy.find(class_='exam-number')
if num_span:
num_span.extract()
# Also extract any images from the copy so they don't leak into text
for img in title_tag_copy.find_all('img'):
img.extract()
q_text = title_tag_copy.get_text().strip()
q_text = re.sub(r'^[\s\.]+', '', q_text).strip()
# Extract passage (if any)
passage = ""
passage_div = box.find(class_='passage')
if passage_div:
passage = html_to_markdown(str(passage_div))
# Extract choices
choices = ["", "", "", ""]
correct_idx = -1
correct_str = ""
correct_answers_serialized = ""
choice_list = box.find(class_='question-choice')
if choice_list:
ol = choice_list.find('ol')
correct_attr = ol.get('correct') if ol else None
li_items = choice_list.find_all('li')
for li_idx, li in enumerate(li_items):
# Check if there is an image in choice
choice_img = li.find('img')
if choice_img:
src = choice_img.get('src')
if src:
local_src = download_and_save_image(src, assets_dir, delay)
choice_text = f'<img src="{local_src}" />'
else:
choice_text = ""
else:
choice_text = li.get_text().strip()
if li_idx < 4:
choices[li_idx] = choice_text
# Check correct choice by class
if 'correct' in li.get('class', []):
correct_idx = li_idx
correct_str = choice_text
# Fallback to correct attribute on ol
if correct_idx == -1 and correct_attr:
try:
correct_idx = int(correct_attr) - 1
if 0 <= correct_idx < len(choices):
correct_str = choices[correct_idx]
except ValueError:
pass
# If it's a descriptive question or no choices were found
if not choice_list or not any(choices):
choices = ["", "", "", ""]
correct_idx = -1
correct_str = "주관식"
correct_answers_serialized = str(correct_idx) if correct_idx != -1 else ""
# Download question image if present
final_image_url = ""
if q_img_url:
final_image_url = download_and_save_image(q_img_url, assets_dir, delay)
# Extract explanations
human_explanations = []
ai_explanations = []
reply_list = box.find(class_='view-reply')
if reply_list:
items = reply_list.find_all(class_='reply-item')
for item in items:
nick_tag = item.find(class_='nick')
nick = nick_tag.get_text().strip() if nick_tag else ""
comment_div = item.find(class_='reply-comment')
if comment_div:
comment_text = html_to_markdown(str(comment_div))
if "AI" in nick or "ai" in nick.lower():
ai_explanations.append(f"### 🤖 {nick} AI 해설\n\n{comment_text}")
else:
human_explanations.append(f"**{nick}**: {comment_text}")
human_explanation = "\n\n---\n\n".join(human_explanations)
ai_explanation = "\n\n---\n\n".join(ai_explanations)
# Construct metadata raw json
meta_json = json.dumps({
"source": "cbtbank.kr",
"q_id": q_id,
"round": round_name,
"subject": current_subject
}, ensure_ascii=False)
# Save to database
cursor = conn.cursor()
try:
cursor.execute('''
INSERT OR REPLACE INTO QuizQuestions (
id, source, category, question_text, choice1, choice2, choice3, choice4,
correct_answer, correct_answer_str, explanation, difficulty, subject,
passage, image_url, raw_json, correct_answers, oid
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
''', (
q_id_int, 'cbtbank', exam_name, q_text,
choices[0], choices[1], choices[2], choices[3],
correct_idx, correct_str, human_explanation, round_name, current_subject,
passage, final_image_url, meta_json, correct_answers_serialized, q_id_int
))
if ai_explanation:
cursor.execute('''
INSERT OR REPLACE INTO QuizExplain (id, source, explain)
VALUES (?, ?, ?)
''', (q_id_int, 'cbtbank', ai_explanation))
conn.commit()
existing_ids.add(q_id_int)
parsed_questions_count += 1
print(f" -> Successfully saved to DB!")
except Exception as db_err:
conn.rollback()
print(f" [DB Error] Failed to save {q_id} (Int: {q_id_int}): {db_err}")
print(f"Completed round {round_name}. Saved {parsed_questions_count} new questions.")
conn.close()
print("\n>>> Scrape operation completed successfully!")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Cbtbank Scraper for Quiz Database")
parser.add_argument("--exam", type=str, default="정보통신기사", help="Name of the exam/category on cbtbank.kr (e.g. 정보통신기사)")
parser.add_argument("--rounds", type=str, default="", help="Comma-separated round names/IDs to scrape (e.g. 'cey20230617'). Default is all.")
parser.add_argument("--overwrite", action="store_true", help="Overwrite existing questions in the database")
parser.add_argument("--delay", type=float, default=1.0, help="Delay in seconds between requests (default: 1.0)")
parser.add_argument("--db", type=str, default="qple_quiz.db", help="Path to sqlite database file (default: qple_quiz.db)")
parser.add_argument("--assets", type=str, default="./frontend/public/assets", help="Path to assets directory to store downloaded images")
args = parser.parse_args()
selected = [r.strip() for r in args.rounds.split(',') if r.strip()] if args.rounds else None
try:
scrape_exam(
exam_name=args.exam,
selected_rounds=selected,
overwrite=args.overwrite,
delay=args.delay,
db_file=args.db,
assets_dir=args.assets
)
except KeyboardInterrupt:
print("\n[Interrupted] Scraper stopped by user.")
sys.exit(0)