app.py

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()