Update app.py

app.py

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+import requests
+from bs4 import BeautifulSoup
+import pandas as pd
+import gradio as gr
+
+# 스크래핑 함수
+def scrape_naver_stock():
+    url = "https://finance.naver.com/sise/sise_rise.naver?sosok=1"
+    response = requests.get(url)
+    response.encoding = 'euc-kr'
+    
+    # BeautifulSoup으로 HTML 파싱
+    soup = BeautifulSoup(response.text, 'html.parser')
+    table = soup.find('table', class_='type_2')
+    
+    # 테이블에서 데이터 추출
+    rows = table.find_all('tr')
+    data = []
+    for row in rows:
+        cols = row.find_all('td')
+        if len(cols) > 1:
+            rank = cols[0].text.strip()
+            name = cols[1].text.strip()
+            price = cols[2].text.strip()
+            diff = cols[3].text.strip()
+            change_rate = cols[4].text.strip()
+            volume = cols[5].text.strip()
+            buy_price = cols[6].text.strip()
+            sell_price = cols[7].text.strip()
+            buy_volume = cols[8].text.strip()
+            sell_volume = cols[9].text.strip()
+            per = cols[10].text.strip()
+            roe = cols[11].text.strip()
+            data.append([rank, name, price, diff, change_rate, volume, buy_price, sell_price, buy_volume, sell_volume, per, roe])
+    
+    # Pandas DataFrame으로 변환
+    df = pd.DataFrame(data, columns=['순위', '종목명', '현재가', '전일비', '등락률', '거래량', '매수호가', '매도호가', '매수총잔량', '매도총잔량', 'PER', 'ROE'])
+    
+    return df
+
+# 그라디오 UI
+def display_stocks():
+    df = scrape_naver_stock()
+    return df
+
+iface = gr.Interface(fn=display_stocks, inputs=[], outputs="dataframe")
+iface.launch()