app.py

import streamlit as st
import yfinance as yf
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
import twstock
from datetime import datetime, timedelta

def plot_stock_data(stock_symbols, period='1y'):
    """
    繪製股票價格圖表
    :param stock_symbols: 股票代號列表
    :param period: 時間區間
    :return: Plotly figure
    """
    # 創建子圖
    fig = make_subplots(
        rows=len(stock_symbols),
        cols=1,
        subplot_titles=[f"股價走勢: {symbol}" for symbol in stock_symbols],
        vertical_spacing=0.05,
        specs=[[{"secondary_y": True}] for _ in stock_symbols]
    )

    # 為每個股票繪製圖形
    for idx, symbol in enumerate(stock_symbols, 1):
        try:
            # 獲取股票數據
            stock = yf.Ticker(symbol)
            df = stock.history(period=period)

            if df.empty:
                st.warning(f"無法找到 {symbol} 的股票數據")
                continue

            # 添加蠟燭圖
            fig.add_trace(
                go.Candlestick(
                    x=df.index,
                    open=df['Open'],
                    high=df['High'],
                    low=df['Low'],
                    close=df['Close'],
                    name=f'{symbol} 價格'
                ),
                row=idx, col=1
            )

            # 添加成交量柱狀圖
            fig.add_trace(
                go.Bar(
                    x=df.index,
                    y=df['Volume'],
                    name=f'{symbol} 成交量',
                    opacity=0.3
                ),
                row=idx, col=1,
                secondary_y=True
            )

            # 添加移動平均線
            for ma_days in [5, 20, 60]:
                ma = df['Close'].rolling(window=ma_days).mean()
                fig.add_trace(
                    go.Scatter(
                        x=df.index,
                        y=ma,
                        name=f'{symbol} MA{ma_days}',
                        line=dict(width=1)
                    ),
                    row=idx, col=1
                )

        except Exception as e:
            st.error(f"處理 {symbol} 時發生錯誤: {str(e)}")

    # 更新布局
    fig.update_layout(
        height=400 * len(stock_symbols),
        title_text="台股分析圖",
        showlegend=True,
        xaxis_rangeslider_visible=False,
        template="plotly_white"
    )

    # 更新軸標籤
    for i in range(1, len(stock_symbols) + 1):
        fig.update_xaxes(title_text="日期", row=i, col=1)
        fig.update_yaxes(title_text="價格 (TWD)", row=i, col=1)
        fig.update_yaxes(title_text="成交量", row=i, col=1, secondary_y=True)

    return fig

def fetch_recent_stock_data(stock_code):
    """
    使用 twstock 獲取近期股票交易數據
    """
    try:
        stock = twstock.Stock(stock_code)
        recent_data = stock.fetch_31()  # 抓取最近 31 天的交易數據

        if not recent_data:
            st.warning(f"無法找到 {stock_code} 的交易數據。")
            return None

        # 將數據整理為 DataFrame 格式
        data_list = [
            {
                "Date": data.date.strftime('%Y-%m-%d'),
                "Open": data.open,
                "High": data.high,
                "Low": data.low,
                "Close": data.close,
                "Transaction": data.transaction,
                "Capacity": data.capacity,
                "Turnover": data.turnover
            }
            for data in recent_data
        ]
        df = pd.DataFrame(data_list)
        return df

    except Exception as e:
        st.error(f"發生錯誤: {e}")
        return None

def main():
    st.set_page_config(page_title="台股分析工具", page_icon=":chart_with_upwards_trend:", layout="wide")
    
    st.title("🚀 台股分析工具")

    # 側邊欄設置
    with st.sidebar:
        st.header("股票分析設定")
        
        # 股票代碼輸入
        stock_input = st.text_input(
            "股票代號 (用逗號分隔)",
            value="2330.TW,2454.TW",
            placeholder="例如: 2330.TW,2454.TW"
        )
        
        # 時間區間選擇
        period_select = st.selectbox(
            "選擇時間區間",
            ["1mo", "3mo", "6mo", "1y", "2y", "5y", "max"],
            index=3  # 預設為 1y
        )

    # 股票分析頁籤
    tab1, tab2 = st.tabs(["股價走勢圖", "近期交易數據"])

    with tab1:
        # 股價走勢圖
        if st.button("繪製股價走勢圖"):
            # 處理股票代號
            stocks = [s.strip() for s in stock_input.split(',')]
            stocks = [f"{s}.TW" if not s.endswith('.TW') and s.isdigit() else s for s in stocks]
            
            # 創建圖表
            fig = plot_stock_data(stocks, period_select)
            st.plotly_chart(fig, use_container_width=True)

    with tab2:
        # 近期交易數據
        st.subheader("個股近期交易數據")
        
        single_stock_code = st.text_input(
            "請輸入股票代碼",
            placeholder="例如: 2330"
        )
        
        if st.button("查詢交易數據"):
            if single_stock_code:
                # 獲取近期股票數據
                df = fetch_recent_stock_data(single_stock_code)
                
                if df is not None:
                    # 顯示數據
                    st.dataframe(df)
                    
                    # 統計資訊
                    st.subheader("基本統計")
                    col1, col2, col3 = st.columns(3)
                    
                    with col1:
                        st.metric("平均收盤價", f"{df['Close'].mean():.2f}")
                    
                    with col2:
                        st.metric("最高價", f"{df['High'].max():.2f}")
                    
                    with col3:
                        st.metric("最低價", f"{df['Low'].min():.2f}")
                    
                    # 匯出 CSV
                    csv_data = df.to_csv(index=False).encode('utf-8-sig')
                    st.download_button(
                        label="下載CSV",
                        data=csv_data,
                        file_name=f"{single_stock_code}_recent_30days.csv",
                        mime="text/csv"
                    )

if __name__ == "__main__":
    main()