galaxis-po/backend/scripts/seed_data.py

"""
One-time script to import historical portfolio data.

Builds portfolio from actual trade history with accurate average prices
and cumulative holdings.

Usage:
    cd backend && python -m scripts.seed_data

Requires: DATABASE_URL environment variable or default dev connection.
"""
import sys
import os
from datetime import date, datetime
from decimal import Decimal, ROUND_HALF_UP

# Add backend to path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from sqlalchemy.orm import Session
from app.core.database import SessionLocal
from app.models.portfolio import (
    Portfolio, PortfolioType, Target, Holding,
    Transaction, TransactionType,
)
from app.models.user import User


# ETF name -> ticker mapping
ETF_MAP = {
    "TIGER 200": "102110",
    "KIWOOM 국고채10년": "148070",
    "KODEX 200미국채혼합": "284430",
    "TIGER 미국S&P500": "360750",
    "ACE KRX금현물": "411060",
}

# Target ratios (percentage of total portfolio)
TARGETS = {
    "102110": Decimal("0.83"),
    "148070": Decimal("25"),
    "284430": Decimal("41.67"),
    "360750": Decimal("17.5"),
    "411060": Decimal("15"),
}

# Actual trade history (date, name, quantity, price_per_unit)
TRADES = [
    # 2025-04-29: Initial purchases
    (date(2025, 4, 29), "ACE KRX금현물", 1, Decimal("21620")),
    (date(2025, 4, 29), "TIGER 미국S&P500", 329, Decimal("19770")),
    (date(2025, 4, 29), "KIWOOM 국고채10년", 1, Decimal("118000")),
    (date(2025, 4, 29), "TIGER 200", 16, Decimal("33815")),
    (date(2025, 4, 30), "KODEX 200미국채혼합", 355, Decimal("13235")),

    # 2025-05-13 ~ 05-16
    (date(2025, 5, 13), "ACE KRX금현물", 260, Decimal("20820")),
    (date(2025, 5, 13), "KODEX 200미국채혼합", 14, Decimal("13165")),
    (date(2025, 5, 14), "ACE KRX금현물", 45, Decimal("20760")),
    (date(2025, 5, 14), "TIGER 미국S&P500", 45, Decimal("20690")),
    (date(2025, 5, 14), "KODEX 200미국채혼합", 733, Decimal("13220")),
    (date(2025, 5, 14), "KIWOOM 국고채10년", 90, Decimal("116939")),
    (date(2025, 5, 16), "KODEX 200미국채혼합", 169, Decimal("13125")),

    # 2025-06-12
    (date(2025, 6, 12), "ACE KRX금현물", 14, Decimal("20855")),
    (date(2025, 6, 12), "TIGER 미국S&P500", 3, Decimal("20355")),
    (date(2025, 6, 12), "KODEX 200미국채혼합", 88, Decimal("13570")),
    (date(2025, 6, 12), "KIWOOM 국고채10년", 5, Decimal("115945")),

    # 2025-07-30
    (date(2025, 7, 30), "KIWOOM 국고채10년", 6, Decimal("116760")),

    # 2025-08-14 ~ 08-19
    (date(2025, 8, 14), "ACE KRX금현물", 6, Decimal("21095")),
    (date(2025, 8, 14), "TIGER 미국S&P500", 3, Decimal("22200")),
    (date(2025, 8, 14), "KODEX 200미국채혼합", 27, Decimal("14465")),
    (date(2025, 8, 14), "KIWOOM 국고채10년", 1, Decimal("117075")),
    (date(2025, 8, 19), "ACE KRX금현물", 2, Decimal("21030")),

    # 2025-10-13
    (date(2025, 10, 13), "TIGER 미국S&P500", 3, Decimal("23480")),
    (date(2025, 10, 13), "KIWOOM 국고채10년", 12, Decimal("116465")),

    # 2025-12-05
    (date(2025, 12, 5), "KIWOOM 국고채10년", 7, Decimal("112830")),

    # 2026-01-07 ~ 01-08
    (date(2026, 1, 7), "TIGER 미국S&P500", 2, Decimal("25015")),
    (date(2026, 1, 8), "KIWOOM 국고채10년", 11, Decimal("109527")),

    # 2026-02-20
    (date(2026, 2, 20), "TIGER 미국S&P500", 20, Decimal("24685")),
    (date(2026, 2, 20), "KIWOOM 국고채10년", 9, Decimal("108500")),

    # 2026-03-23
    (date(2026, 3, 23), "ACE KRX금현물", 41, Decimal("30095")),
    (date(2026, 3, 23), "TIGER 미국S&P500", 128, Decimal("24290")),
    (date(2026, 3, 23), "KODEX 200미국채혼합", 188, Decimal("19579")),
    (date(2026, 3, 23), "KIWOOM 국고채10년", 10, Decimal("106780")),
]


def _compute_holdings(trades: list) -> dict:
    """Compute current holdings with weighted average prices from trade history."""
    holdings = {}
    for _, name, qty, price in trades:
        ticker = ETF_MAP[name]
        if ticker not in holdings:
            holdings[ticker] = {"qty": 0, "total_cost": Decimal("0")}
        holdings[ticker]["qty"] += qty
        holdings[ticker]["total_cost"] += qty * price
    return holdings


def seed(db: Session):
    """Import historical data into database."""
    # Find admin user (first user in DB)
    user = db.query(User).first()
    if not user:
        print("ERROR: No user found in database. Create a user first.")
        return

    # Delete existing portfolio if present (cascade deletes related records)
    existing = db.query(Portfolio).filter(
        Portfolio.user_id == user.id,
        Portfolio.name == "연금 포트폴리오",
    ).first()
    if existing:
        db.delete(existing)
        db.flush()
        print(f"Deleted existing portfolio (id={existing.id})")

    # Create portfolio
    portfolio = Portfolio(
        user_id=user.id,
        name="연금 포트폴리오",
        portfolio_type=PortfolioType.PENSION,
    )
    db.add(portfolio)
    db.flush()
    print(f"Created portfolio id={portfolio.id}")

    # Set targets
    for ticker, ratio in TARGETS.items():
        db.add(Target(portfolio_id=portfolio.id, ticker=ticker, target_ratio=ratio))
    print(f"Set {len(TARGETS)} targets")

    # Create transactions from trade history
    tx_count = 0
    for trade_date, name, qty, price in TRADES:
        ticker = ETF_MAP[name]
        db.add(Transaction(
            portfolio_id=portfolio.id,
            ticker=ticker,
            tx_type=TransactionType.BUY,
            quantity=qty,
            price=price,
            executed_at=datetime.combine(trade_date, datetime.min.time()),
            memo=f"{name} 매수",
        ))
        tx_count += 1
    print(f"Created {tx_count} transactions")

    # Set current holdings from computed totals
    computed = _compute_holdings(TRADES)
    for ticker, data in computed.items():
        qty = data["qty"]
        avg_price = (data["total_cost"] / qty).quantize(Decimal("0.01"), rounding=ROUND_HALF_UP)
        db.add(Holding(
            portfolio_id=portfolio.id,
            ticker=ticker,
            quantity=qty,
            avg_price=avg_price,
        ))
    print(f"Set {len(computed)} current holdings")

    # Print summary
    print("\n=== Holdings Summary ===")
    total_invested = Decimal("0")
    for ticker in sorted(computed.keys()):
        d = computed[ticker]
        avg = (d["total_cost"] / d["qty"]).quantize(Decimal("0.01"), rounding=ROUND_HALF_UP)
        name = [n for n, t in ETF_MAP.items() if t == ticker][0]
        print(f"  {name:20s} ({ticker})  qty={d['qty']:>5d}  avg={avg:>12}  invested={d['total_cost']:>15}")
        total_invested += d["total_cost"]
    print(f"  {'TOTAL':20s}              invested={total_invested:>15}")

    db.commit()
    print("\nDone!")


if __name__ == "__main__":
    db = SessionLocal()
    try:
        seed(db)
    finally:
        db.close()