app.py

import streamlit as st
import requests
from bs4 import BeautifulSoup
import pandas as pd
import plotly.express as px
import time

def main():
    st.set_page_config(page_title="奇美醫院病床占用率查詢", layout="wide")
    
    st.title("奇美醫院病床占用率查詢系統")
    st.write("此應用程式顯示奇美醫院的即時病床占用情況")
    
    # 添加刷新按鈕
    if st.button("刷新數據"):
        st.cache_data.clear()
    
    # 獲取病床數據
    df = get_hospital_bed_data()
    
    # 如果數據獲取失敗，提供示例數據
    if df.empty:
        st.warning("⚠️ 無法連接到奇美醫院網站。顯示示例數據以供參考。")
        df = get_sample_data()
    
    # 顯示數據
    col1, col2 = st.columns([2, 3])
    
    with col1:
        st.subheader("病床占用數據表")
        st.dataframe(df, use_container_width=True)
        
        # 計算總數
        total_beds = df['總床數'].sum()
        total_occupied = df['佔床數'].sum()
        total_available = df['空床數'].sum()
        overall_rate = f"{(total_occupied / total_beds * 100):.2f}%" if total_beds > 0 else "0%"
        
        st.subheader("總計")
        total_data = pd.DataFrame({
            '項目': ['總病床數', '總佔床數', '總空床數', '整體佔床率'],
            '數值': [total_beds, total_occupied, total_available, overall_rate]
        })
        st.dataframe(total_data, use_container_width=True, hide_index=True)
    
    with col2:
        st.subheader("病床占用率視覺化")
        
        # 創建占用率條形圖
        fig = px.bar(
            df,
            x='病床類別',
            y='佔床數',
            text='佔床率',
            color='佔床率',
            color_continuous_scale='RdYlGn_r',  # 紅(高)-黃-綠(低)色彩範圍
            labels={'佔床數': '已占用病床數', '病床類別': '病床類型', '佔床率': '占用率'},
            height=500
        )
        fig.update_layout(xaxis={'categoryorder': 'total descending'})
        st.plotly_chart(fig, use_container_width=True)
        
        # 創建餅圖顯示空床/占床比例
        pie_data = pd.DataFrame({
            '狀態': ['已占用', '可用'],
            '數量': [total_occupied, total_available]
        })
        pie_fig = px.pie(
            pie_data, 
            values='數量', 
            names='狀態',
            color='狀態',
            color_discrete_map={'已占用': 'red', '可用': 'green'},
            hole=0.4
        )
        st.plotly_chart(pie_fig, use_container_width=True)

@st.cache_data(ttl=300)  # 資料快取5分鐘
def get_hospital_bed_data():
    """獲取奇美醫院病床占用數據"""
    try:
        # URL of the page to scrape
        url = "https://www.chimei.org.tw/%E4%BD%94%E5%BA%8A%E7%8E%87%E6%9F%A5%E8%A9%A2/%E4%BD%94%E5%BA%8A%E7%8E%87%E6%9F%A5%E8%A9%A2.aspx?ihospital=10&ffloor="
        
        # 設置請求頭，模擬瀏覽器訪問
        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',
            'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
            'Accept-Language': 'zh-TW,zh;q=0.9,en-US;q=0.8,en;q=0.7',
            'Connection': 'keep-alive',
            'Upgrade-Insecure-Requests': '1',
            'Referer': 'https://www.chimei.org.tw/'
        }
        
        # Send HTTP request with timeout and headers
        response = requests.get(url, headers=headers, timeout=10)
        response.encoding = 'utf-8'  # Set encoding to handle Chinese characters
        
        # Create BeautifulSoup object
        soup = BeautifulSoup(response.text, 'html.parser')
        
        # Find the target table (DG1)
        target_table = soup.find('table', {'id': 'DG1'})
        
        # Extract data from the table
        data = []
        if target_table:
            rows = target_table.find_all('tr')
            
            # Skip the header row
            for row in rows[1:]:
                cols = row.find_all('td')
                if len(cols) == 5:  # Ensure row has 5 columns
                    bed_type = cols[0].text.strip()
                    total_beds = int(cols[1].text.strip())
                    occupied_beds = int(cols[2].text.strip())
                    available_beds = int(cols[3].text.strip())
                    occupancy_rate = cols[4].text.strip()
                    
                    data.append({
                        '病床類別': bed_type,
                        '總床數': total_beds,
                        '佔床數': occupied_beds,
                        '空床數': available_beds,
                        '佔床率': occupancy_rate
                    })
        
        # Create pandas DataFrame
        df = pd.DataFrame(data)
        return df
    
    except Exception as e:
        st.error(f"獲取數據時發生錯誤: {e}")
        return pd.DataFrame()

def get_sample_data():
    """提供示例數據，當無法從網站獲取數據時使用"""
    data = [
        {'病床類別': '一般病床', '總床數': 1200, '佔床數': 980, '空床數': 220, '佔床率': '81.67%'},
        {'病床類別': '加護病床', '總床數': 120, '佔床數': 98, '空床數': 22, '佔床率': '81.67%'},
        {'病床類別': '燒燙傷病床', '總床數': 30, '佔床數': 18, '空床數': 12, '佔床率': '60.00%'},
        {'病床類別': '負壓隔離病床', '總床數': 24, '佔床數': 10, '空床數': 14, '佔床率': '41.67%'},
        {'病床類別': '急診觀察病床', '總床數': 60, '佔床數': 45, '空床數': 15, '佔床率': '75.00%'},
        {'病床類別': '精神科病床', '總床數': 80, '佔床數': 65, '空床數': 15, '佔床率': '81.25%'}
    ]
    return pd.DataFrame(data)

if __name__ == "__main__":
    main()