yongxiang9921/IPO

1import streamlit as st2import pandas as pd3import plotly.express as px4import time5from datetime import datetime6import db_manager  # 引入我们的后端模块7 8# --- 1. 系统初始化 (System Init) ---9st.set_page_config(10    page_title="iPO Terminal - Asset Liquidation",11    page_icon="📉",12    layout="wide",13    initial_sidebar_state="expanded"14)15 16# 确保数据库已存在17db_manager.init_db()18 19# --- CSS 样式植入：金融极客风 ---20st.markdown("""21    <style>22    .stApp { background-color: #0E1117; color: #00FF41; }23    .stMetricValue { font-family: 'Courier New', monospace; font-weight: bold; color: #00FF41 !important; }24    /* 红色卖出按钮 */25    div.stButton > button {26        background-color: #FF4B4B; color: white; width: 100%;27        border-radius: 0px; border: 1px solid #FF0000;28        font-family: 'Courier New'; font-weight: bold; font-size: 20px;29    }30    div.stButton > button:hover { background-color: #FF0000; border-color: white; }31    </style>32    """, unsafe_allow_html=True)33 34# --- 2. 侧边栏：交易控制台 (Trading Floor) ---35with st.sidebar:36    st.title("💸 TRADING FLOOR")37    st.caption("Human Capital Liquidation System")38    st.markdown("---")39 40    # [新增] 薪资设置 - 用于计算收益 (折叠起来，保护隐私)41    with st.expander("⚙️ 财务参数 (Financial Params)"):42        monthly_salary = st.number_input("月薪 (Monthly Salary)", value=10000, step=1000,43                                         help="用于计算你的带薪拉屎收益 (EPS)")44        # 估算每分钟价值：月薪 / 21.75天 / 8小时 / 60分钟45        money_per_min = monthly_salary / 21.75 / 8 / 6046        st.caption(f"当前估值: ¥{money_per_min:.2f} / min")47 48    st.markdown("### 📝 委托单 (Order Entry)")49 50    # 1. 资产类型51    asset_options = [52        "牛市 : 完美的一条",53        "熊市 : 稀烂（腹泻",54        "流动性紧缩 : 便秘，拉不出来"55        "通货膨胀 : 只是放了很多屁，实际上没货"56    ]57    asset_type = st.selectbox("资产类别 (Asset Class)", options=asset_options)58 59    # 2. 交易参数60    col1, col2 = st.columns(2)61    with col1:62        volume = st.slider("成交量 (Vol)", 1, 10, 5,help="1=微量，10=清仓")63    with col2:64        volatility = st.slider("波动率 (Effort)", 1, 10, 3,help="用力程度，1=顺畅，10=拉不出来")65 66    duration = st.number_input("持仓时长 (Duration/Min)", min_value=1.0, value=10.0, step=0.5)67 68    # 计算本次预计收益69    estimated_profit = money_per_min * duration70    st.info(f"💰 预计资金回笼: ¥{estimated_profit:.2f}")71 72    st.markdown("---")73 74    # 3. 执行按钮75    if st.button("🔴 EXECUTE SELL (确认抛售)"):76        with st.spinner('正在连接直肠交易所...'):77            time.sleep(0.8)  # 仪式感延迟78 79            # 调用后端写入数据库80            db_manager.execute_trade(81                asset_class=asset_type.split(" (")[0],  # 只存英文名简写82                volume=volume,83                volatility=volatility,84                duration_min=duration,85                net_profit=round(estimated_profit, 2)86            )87 88        st.toast(f"✅ 交易成功！入账 ¥{estimated_profit:.2f}", icon="🤑")89        time.sleep(1)  # 等待一秒让用户看清提示90        st.rerun()  # 刷新页面，显示最新数据91 92# --- 3. 主界面：市场概览 (Market Overview) ---93 94st.title("📊 iPO (Initial Poop Offering) Dashboard")95st.markdown(f"**Status:** `MARKET OPEN` | **Trader:** `You` | **Date:** `{datetime.now().strftime('%Y-%m-%d')}`")96 97# 读取数据库数据98raw_data = db_manager.fetch_history()99df = pd.DataFrame(raw_data)100 101if df.empty:102    st.warning("⚠️ 市场休市中：暂无交易记录。请在左侧侧边栏发起你的第一次 IPO。")103else:104    # 转换时间格式，方便绘图105    df['timestamp'] = pd.to_datetime(df['timestamp'])106 107    # --- A. 顶部核心指标 (KPIs) ---108    col1, col2, col3, col4 = st.columns(4)109 110    total_profit = df['net_profit'].sum()111    total_duration = df['duration_min'].sum()112    avg_effort = df['volatility'].mean()113    last_trade_time = df['timestamp'].iloc[0]114 115    # 计算距离上一次的时间差116    time_diff = datetime.now() - last_trade_time117    hours_since = time_diff.total_seconds() / 3600118 119    with col1:120        st.metric("累计收益 (Total Earnings)", f"¥ {total_profit:,.2f}", help="也就是公司付钱请你拉屎的总金额")121    with col2:122        st.metric("总工时 (Total Hours)", f"{total_duration / 60:.1f} hrs", help="你在厕所度过的总时间")123    with col3:124        # 如果超过24小时没拉，变成红色警告125        sentiment = "Bearish (便秘风险)" if hours_since > 24 else "Bullish (通畅)"126        delta_color = "inverse" if hours_since > 24 else "normal"127        st.metric("上次交割 (Last Trade)", f"{hours_since:.1f} hrs ago", delta=sentiment, delta_color=delta_color)128    with col4:129        st.metric("平均压力 (Avg RSI)", f"{avg_effort:.1f}/10", help="平均括约肌努力程度")130 131    st.markdown("---")132 133    # --- B. 专业图表区 (Technical Analysis) ---134    c1, c2 = st.columns([2, 1])135 136    with c1:137        st.subheader("📈 收益走势 (Earnings Trend)")138        # 使用 Plotly 画更高级的面积图139        fig_trend = px.area(140            df,141            x='timestamp',142            y='net_profit',143            color='asset_class',144            title='Net Profit over Time by Asset Class',145            template="plotly_dark",146            color_discrete_sequence=px.colors.qualitative.Pastel147        )148        st.plotly_chart(fig_trend, use_container_width=True)149 150    with c2:151        st.subheader("🍰 资产分布 (Portfolio)")152        fig_pie = px.pie(153            df,154            names='asset_class',155            values='duration_min',156            hole=0.4,157            template="plotly_dark",158            color_discrete_sequence=px.colors.qualitative.Set3159        )160        fig_pie.update_layout(showlegend=False, margin=dict(t=0, b=0, l=0, r=0))161        st.plotly_chart(fig_pie, use_container_width=True)162 163    # --- C. 详细账本 (Ledger) ---164    with st.expander("📜 查看历史交割单 (Transaction History)", expanded=True):165        # 格式化一下显示，让它更好看166        display_df = df[['timestamp', 'asset_class', 'duration_min', 'net_profit', 'volatility']].copy()167        display_df.columns = ['Time', 'Asset Type', 'Duration (min)', 'Earnings (¥)', 'Effort (1-10)']168 169        st.dataframe(170            display_df.style.background_gradient(subset=['Earnings (¥)'], cmap='Greens'),171            use_container_width=True,172            hide_index=True173        )174 175# 底部免责声明176st.markdown("---")177st.caption(178    "Investment Advice: High volatility in the morning is expected. Please maintain adequate fiber intake to ensure market liquidity.")179