import requests
import json
import pandas as pd
import time
import streamlit as st
import plotly.express as px
import plotly.graph_objects as go

# Streamlit title and input
st.title("2024 0925 PCHOME 商品價格分析")
keyword = st.text_input("請輸入商品關鍵字", value="平板")  # default keyword is "平板"
pages = st.number_input("要抓取的頁數", min_value=1, max_value=5, value=2, step=1)

# Fetch data only when button is clicked
if st.button("抓取數據"):
    alldata = pd.DataFrame()

    # Start timer to calculate execution time
    start_time = time.time()

    for i in range(1, pages + 1):  # Grab data from specified number of pages
        url = f'https://ecshweb.pchome.com.tw/search/v3.3/all/results?q={keyword}&page={i}&sort=sale/dc'
        list_req = requests.get(url)
        getdata = json.loads(list_req.content)
        todataFrame = pd.DataFrame(getdata['prods'])  # Convert to DataFrame
        alldata = pd.concat([alldata, todataFrame], ignore_index=True)  # Concatenate data
        time.sleep(1)  # Simulate delay to avoid overloading server

    # Data Processing and Analysis
    df = alldata[["name", "price"]]

    # Calculate average price
    average_price = df['price'].mean()

    # Display the fetched data in Streamlit
    st.subheader(f"抓取到 {len(df)} 條商品數據")
    st.dataframe(df)

    # Plotly Bar Chart
    st.subheader("商品價格分佈 (柱狀圖)")
    fig = px.bar(df[:70], x=df.index[:70], y='price', text='price',
                 title=f'PCHOME 上 "{keyword}" 商品售價',
                 labels={'price': '價格 (元)', 'index': '商品編號'})

    fig.update_traces(marker_color='skyblue', textposition='outside')

    # Add a horizontal line for average price
    fig.add_hline(y=average_price, line_dash="dash", line_color="red",
                  annotation_text=f'平均售價: {average_price:.1f}', annotation_position="bottom right")

    # Display Bar Chart
    st.plotly_chart(fig)

    # Plotly Pie Chart for Price Distribution
    st.subheader("商品價格分佈 (圓餅圖)")
    df['price_range'] = pd.cut(df['price'], bins=[0, 5000, 10000, 15000, 20000, float('inf')],
                               labels=['0-5k', '5k-10k', '10k-15k', '15k-20k', '20k以上'])
    pie_chart = px.pie(df, names='price_range', title='商品價格分佈')
    st.plotly_chart(pie_chart)

    # Plotly Sunburst Chart for Price Range and Product Name
    st.subheader("商品價格與名稱的 Sunburst 圖")
    sunburst_chart = px.sunburst(df[:70], path=['price_range', 'name'], values='price',
                                 title='商品價格與名稱分佈 (Sunburst 圖)')
    st.plotly_chart(sunburst_chart)

    # Calculate and display execution time
    end_time = time.time()
    execution_time = end_time - start_time
    st.write(f"執行時間：{execution_time:.2f} 秒")