first vibe coding

2026-05-14 15:14:50 +09:00
commit bfff65e55b
40 changed files with 2795 additions and 0 deletions
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+"""
+monitor/dashboard.py - Streamlit 대시보드
+실행: streamlit run monitor/dashboard.py --server.port 8501
+"""
+import streamlit as st
+import pandas as pd
+import sqlite3
+import json
+import os
+from datetime import datetime, timedelta
+
+DB_PATH = os.getenv("DB_PATH", "data/stockbot.db")
+AI_CTX  = os.getenv("AI_CONTEXT_PATH", "data/daily_context.json")
+
+st.set_page_config(page_title="단타봇 대시보드", layout="wide")
+st.title("📈 단타 자동매매 대시보드")
+st.caption(f"마지막 갱신: {datetime.now().strftime('%H:%M:%S')}")
+
+# ── AI 판단 현황 ──
+st.subheader("🤖 오늘의 AI 판단")
+try:
+    with open(AI_CTX, encoding="utf-8") as f:
+        ctx = json.load(f)
+    col1, col2, col3, col4 = st.columns(4)
+    col1.metric("시장 분위기", ctx.get("market_sentiment", "-"))
+    col2.metric("감성 점수",   f"{ctx.get('sentiment_score', 0)}점")
+    col3.metric("리스크 레벨", ctx.get("risk_level", "-"))
+    col4.metric("거래 허용",   "✅" if ctx.get("trade_allowed") else "❌")
+    st.info(f"💬 {ctx.get('reason', '')}")
+    col_l, col_r = st.columns(2)
+    col_l.write(f"**주목 섹터:** {', '.join(ctx.get('hot_sectors', []))}")
+    col_r.write(f"**회피 섹터:** {', '.join(ctx.get('avoid_sectors', []))}")
+except:
+    st.warning("AI 판단 데이터 없음 (08:00 이후 생성)")
+
+st.divider()
+
+# ── 오늘 매매 현황 ──
+st.subheader("📊 오늘 매매 현황")
+try:
+    conn  = sqlite3.connect(DB_PATH)
+    today = datetime.now().strftime("%Y-%m-%d")
+    df    = pd.read_sql(
+        "SELECT * FROM trades WHERE date=?", conn, params=(today,)
+    )
+    conn.close()
+
+    if df.empty:
+        st.info("오늘 매매 없음")
+    else:
+        total  = len(df)
+        wins   = (df["pnl"] > 0).sum()
+        net    = df["pnl"].sum()
+        win_rt = wins / total * 100 if total else 0
+
+        c1, c2, c3, c4 = st.columns(4)
+        c1.metric("총 매매", f"{total}회")
+        c2.metric("승률",    f"{win_rt:.0f}%")
+        c3.metric("순손익",  f"{net:+,.0f}원")
+        c4.metric("승/패",   f"{wins}/{total-wins}")
+        st.dataframe(df[["entry_time","ticker","name","entry_price",
+                          "exit_price","pnl","exit_reason"]].fillna("-"),
+                     use_container_width=True)
+except Exception as e:
+    st.error(f"DB 연결 실패: {e}")
+
+st.divider()
+
+# ── 주간 손익 ──
+st.subheader("📅 최근 7일 손익")
+try:
+    conn = sqlite3.connect(DB_PATH)
+    week_ago = (datetime.now() - timedelta(days=7)).strftime("%Y-%m-%d")
+    df_w = pd.read_sql(
+        "SELECT date, SUM(pnl) as net_pnl, COUNT(*) as trades "
+        "FROM trades WHERE date >= ? GROUP BY date ORDER BY date",
+        conn, params=(week_ago,)
+    )
+    conn.close()
+    if not df_w.empty:
+        st.bar_chart(df_w.set_index("date")["net_pnl"])
+        st.dataframe(df_w, use_container_width=True)
+except:
+    st.info("주간 데이터 없음")
+
+st.button("🔄 새로고침", on_click=st.rerun)