app.py

import streamlit as st
import requests
from bs4 import BeautifulSoup
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from google.oauth2.service_account import Credentials
import gspread

# 爬取 Booking.com 台南飯店數據
def scrape_booking_hotel():
    url = "https://www.booking.com/searchresults.zh-tw.html"
    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-Language': 'zh-TW,zh;q=0.9,en-US;q=0.8,en;q=0.7',
    }
    params = {
        'ss': '台南',
        'checkin': '2024-11-16',
        'checkout': '2024-11-17',
        'group_adults': '2',
        'no_rooms': '1',
        'group_children': '0',
        'dest_id': '-2637868',
        'dest_type': 'city'
    }

    try:
        response = requests.get(url, headers=headers, params=params)
        response.raise_for_status()
        soup = BeautifulSoup(response.text, 'html.parser')

        hotels_data = []
        hotel_cards = soup.find_all('div', {'data-testid': 'property-card'})

        for hotel in hotel_cards:
            try:
                name = hotel.find('div', {'data-testid': 'title', 'class': 'f6431b446c'}).text.strip() or "無資料"
                
                price = hotel.find('span', {'data-testid': 'price-and-discounted-price', 'class': 'f6431b446c'}).text.strip() or "無資料"
                price = price.replace('TWD', '').replace(' ', '').replace(',', '').strip()
                price = float(price) if price.replace('.', '', 1).isdigit() else None  # 價格轉為浮點數

                rating_container = hotel.find('div', {'class': 'a3b8729ab1'})
                rating = rating_container.find('div', {'class': 'ac4a7896c7'}).text.strip() if rating_container else "無評分"
                rating = float(rating) if rating.replace('.', '', 1).isdigit() else None  # 評分轉為浮點數

                description_elem = hotel.find('div', {'data-testid': 'recommended-units'})
                if description_elem:
                    room_type = description_elem.find('h4', {'class': 'abf093bdfe'}).text.strip() if description_elem.find('h4', {'class': 'abf093bdfe'}) else ""
                    bed_info = description_elem.find('div', {'class': 'abf093bdfe'}).text.strip() if description_elem.find('div', {'class': 'abf093bdfe'}) else ""
                    cancellation = "可免費取消" if description_elem.find('strong', string='可免費取消') else ""
                    payment = "無需訂金" if description_elem.find('strong', string='無需訂金') else ""
                    description = f"{room_type} | {bed_info} | {cancellation} | {payment}".strip(' |')
                else:
                    description = "無說明"

                hotels_data.append({
                    '飯店名稱': name,
                    '價格': price,
                    '評分': rating,
                    '說明': description
                })

            except AttributeError as e:
                print(f"解析飯店資訊時發生錯誤: {e}")
                continue

        df = pd.DataFrame(hotels_data)
        df = df.drop_duplicates()
        return df

    except requests.RequestException as e:
        print(f"請求發生錯誤: {e}")
        return pd.DataFrame()

# 散佈圖
def create_price_rating_scatter(df):
    fig = px.scatter(
        df,
        x='價格',
        y='評分',
        text='飯店名稱',
        size='價格',
        color='評分',
        title='台南飯店價格與評分關係圖',
        labels={'價格': '房價 (TWD)', '評分': '評分 (0-10)'}
    )
    fig.update_traces(textposition='top center', marker=dict(sizeref=2.*max(df['價格'])/(40.**2)))
    fig.update_layout(height=600, showlegend=True, title_x=0.5, title_font_size=20)
    return fig

# 價格分佈圖
def create_price_distribution(df):
    fig = go.Figure()
    fig.add_trace(go.Histogram(x=df['價格'], name='價格分布', nbinsx=10, marker_color='rgb(55, 83, 109)'))
    fig.add_trace(go.Box(x=df['價格'], name='價格箱型圖', marker_color='rgb(26, 118, 255)'))
    fig.update_layout(title_text='台南飯店價格分布', title_x=0.5, title_font_size=20, xaxis_title='價格 (TWD)', yaxis_title='數量', height=500, bargap=0.2, showlegend=True)
    return fig

# 更新 Google Sheet
def update_google_sheet(df):
    scope = ['https://www.googleapis.com/auth/spreadsheets']
    creds = Credentials.from_service_account_file("realtime-441511-f5708eabdf26.json", scopes=scope)
    gs = gspread.authorize(creds)
    sheet = gs.open_by_url('https://docs.google.com/spreadsheets/d/1tIsXCbB8P6ZxdnZNnv7S7BBWbbT7lrSjW990zG-vQAA/edit?gid=0#gid=0')
    worksheet = sheet.get_worksheet(0)
    worksheet.update([df.columns.values.tolist()] + df.astype(str).values.tolist())
    st.success("Data updated to Google Sheet successfully!")

# 主函數
def main():
    st.set_page_config(page_title="Booking.com Hotel Analysis")
    st.title("Booking.com Hotel Analysis")

    df = scrape_booking_hotel()

    # 顯示資料表格
    st.subheader("Hotel Data")
    st.dataframe(df)

    # 顯示散佈圖
    st.subheader("Price vs Rating Scatter Plot")
    scatter_fig = create_price_rating_scatter(df)
    st.plotly_chart(scatter_fig)

    # 顯示價格分布圖
    st.subheader("Price Distribution")
    dist_fig = create_price_distribution(df)
    st.plotly_chart(dist_fig)

    # Google Sheet 更新
    if st.button("Update Google Sheet"):
        update_google_sheet(df)

if __name__ == "__main__":
    main()