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- New script: scripts/generate_snapshots.py - Fetches actual ETF closing prices from KRX for each month-end - Computes portfolio value from cumulative holdings at each date - Generates 12 monthly snapshots (2025-04 ~ 2026-03) - Added to CI/CD deploy pipeline
264 lines
9.6 KiB
Python
264 lines
9.6 KiB
Python
"""
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Generate portfolio snapshots from trade history using actual market prices.
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Fetches closing prices from KRX (via pykrx) for each snapshot date,
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then computes portfolio value based on cumulative holdings at that point.
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Snapshot dates: end of each month where trades occurred, plus latest available.
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Usage:
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cd backend && python -m scripts.generate_snapshots
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Requires:
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- DATABASE_URL environment variable
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- KRX_ID / KRX_PW environment variables (pykrx >= 1.2.5)
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"""
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import sys
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import os
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import time
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import logging
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from datetime import date, datetime, timedelta
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from decimal import Decimal, ROUND_HALF_UP
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from collections import defaultdict
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from json import JSONDecodeError
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from pykrx import stock as pykrx_stock
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from sqlalchemy.orm import Session
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from app.core.database import SessionLocal
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from app.models.portfolio import (
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Portfolio, PortfolioSnapshot, SnapshotHolding,
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)
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
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logger = logging.getLogger(__name__)
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# ETF name -> ticker mapping (must match seed_data.py)
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ETF_MAP = {
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"TIGER 200": "102110",
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"KIWOOM 국고채10년": "148070",
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"KODEX 200미국채혼합": "284430",
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"TIGER 미국S&P500": "360750",
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"ACE KRX금현물": "411060",
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}
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TICKER_NAMES = {v: k for k, v in ETF_MAP.items()}
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# Trade history (same as seed_data.py)
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TRADES = [
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(date(2025, 4, 29), "ACE KRX금현물", 1, Decimal("21620")),
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(date(2025, 4, 29), "TIGER 미국S&P500", 329, Decimal("19770")),
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(date(2025, 4, 29), "KIWOOM 국고채10년", 1, Decimal("118000")),
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(date(2025, 4, 29), "TIGER 200", 16, Decimal("33815")),
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(date(2025, 4, 30), "KODEX 200미국채혼합", 355, Decimal("13235")),
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(date(2025, 5, 13), "ACE KRX금현물", 260, Decimal("20820")),
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(date(2025, 5, 13), "KODEX 200미국채혼합", 14, Decimal("13165")),
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(date(2025, 5, 14), "ACE KRX금현물", 45, Decimal("20760")),
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(date(2025, 5, 14), "TIGER 미국S&P500", 45, Decimal("20690")),
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(date(2025, 5, 14), "KODEX 200미국채혼합", 733, Decimal("13220")),
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(date(2025, 5, 14), "KIWOOM 국고채10년", 90, Decimal("116939")),
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(date(2025, 5, 16), "KODEX 200미국채혼합", 169, Decimal("13125")),
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(date(2025, 6, 12), "ACE KRX금현물", 14, Decimal("20855")),
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(date(2025, 6, 12), "TIGER 미국S&P500", 3, Decimal("20355")),
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(date(2025, 6, 12), "KODEX 200미국채혼합", 88, Decimal("13570")),
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(date(2025, 6, 12), "KIWOOM 국고채10년", 5, Decimal("115945")),
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(date(2025, 7, 30), "KIWOOM 국고채10년", 6, Decimal("116760")),
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(date(2025, 8, 14), "ACE KRX금현물", 6, Decimal("21095")),
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(date(2025, 8, 14), "TIGER 미국S&P500", 3, Decimal("22200")),
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(date(2025, 8, 14), "KODEX 200미국채혼합", 27, Decimal("14465")),
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(date(2025, 8, 14), "KIWOOM 국고채10년", 1, Decimal("117075")),
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(date(2025, 8, 19), "ACE KRX금현물", 2, Decimal("21030")),
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(date(2025, 10, 13), "TIGER 미국S&P500", 3, Decimal("23480")),
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(date(2025, 10, 13), "KIWOOM 국고채10년", 12, Decimal("116465")),
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(date(2025, 12, 5), "KIWOOM 국고채10년", 7, Decimal("112830")),
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(date(2026, 1, 7), "TIGER 미국S&P500", 2, Decimal("25015")),
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(date(2026, 1, 8), "KIWOOM 국고채10년", 11, Decimal("109527")),
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(date(2026, 2, 20), "TIGER 미국S&P500", 20, Decimal("24685")),
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(date(2026, 2, 20), "KIWOOM 국고채10년", 9, Decimal("108500")),
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(date(2026, 3, 23), "ACE KRX금현물", 41, Decimal("30095")),
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(date(2026, 3, 23), "TIGER 미국S&P500", 128, Decimal("24290")),
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(date(2026, 3, 23), "KODEX 200미국채혼합", 188, Decimal("19579")),
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(date(2026, 3, 23), "KIWOOM 국고채10년", 10, Decimal("106780")),
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]
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def _get_holdings_at_date(target_date: date) -> dict[str, int]:
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"""Compute cumulative holdings at a given date."""
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holdings: dict[str, int] = defaultdict(int)
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for trade_date, name, qty, _ in TRADES:
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if trade_date <= target_date:
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ticker = ETF_MAP[name]
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holdings[ticker] += qty
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return dict(holdings)
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def _generate_snapshot_dates() -> list[date]:
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"""Generate month-end snapshot dates from first trade to today."""
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if not TRADES:
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return []
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first_date = min(t[0] for t in TRADES)
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today = date.today()
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dates = []
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# Month-end dates
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current = date(first_date.year, first_date.month, 1)
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while current <= today:
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# Last day of month
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if current.month == 12:
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next_month = date(current.year + 1, 1, 1)
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else:
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next_month = date(current.year, current.month + 1, 1)
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last_day = next_month - timedelta(days=1)
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# Only include if we have holdings at this date
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if last_day >= first_date and last_day <= today:
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dates.append(last_day)
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current = next_month
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return dates
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def _fetch_price_with_retry(ticker: str, date_str: str, max_retries: int = 3) -> Decimal | None:
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"""Fetch closing price for a ticker on a date, with fallback to previous days."""
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target = datetime.strptime(date_str, "%Y%m%d").date()
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for day_offset in range(5): # Try up to 5 days back (weekends/holidays)
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try_date = target - timedelta(days=day_offset)
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try_date_str = try_date.strftime("%Y%m%d")
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for attempt in range(max_retries):
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try:
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# For ETFs, use get_etf_ohlcv_by_date
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df = pykrx_stock.get_etf_ohlcv_by_date(try_date_str, try_date_str, ticker)
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if df is not None and not df.empty:
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close = df.iloc[0]["종가"]
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if close and float(close) > 0:
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return Decimal(str(int(close)))
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except (JSONDecodeError, ConnectionError, KeyError, ValueError) as e:
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if attempt < max_retries - 1:
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logger.warning(f"Retry {attempt+1}/{max_retries} for {ticker} on {try_date_str}: {e}")
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time.sleep(2)
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continue
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# Fallback: try stock API (for non-ETF tickers)
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for day_offset in range(5):
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try_date = target - timedelta(days=day_offset)
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try_date_str = try_date.strftime("%Y%m%d")
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try:
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df = pykrx_stock.get_market_ohlcv(try_date_str, try_date_str, ticker)
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if df is not None and not df.empty:
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close = df.iloc[0]["종가"]
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if close and float(close) > 0:
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return Decimal(str(int(close)))
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except Exception:
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continue
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return None
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def generate_snapshots(db: Session):
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"""Generate portfolio snapshots from trade history with actual market prices."""
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# Find portfolio
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portfolio = db.query(Portfolio).filter(Portfolio.name == "연금 포트폴리오").first()
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if not portfolio:
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logger.error("Portfolio '연금 포트폴리오' not found. Run seed_data.py first.")
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return
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# Delete existing snapshots
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existing = db.query(PortfolioSnapshot).filter(
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PortfolioSnapshot.portfolio_id == portfolio.id
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).all()
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if existing:
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for snap in existing:
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db.delete(snap)
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db.flush()
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logger.info(f"Deleted {len(existing)} existing snapshots")
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snapshot_dates = _generate_snapshot_dates()
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logger.info(f"Generating {len(snapshot_dates)} snapshots from {snapshot_dates[0]} to {snapshot_dates[-1]}")
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all_tickers = list(ETF_MAP.values())
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created = 0
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for snap_date in snapshot_dates:
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holdings = _get_holdings_at_date(snap_date)
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if not holdings:
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continue
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date_str = snap_date.strftime("%Y%m%d")
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logger.info(f"Processing {snap_date} ({len(holdings)} tickers)...")
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# Fetch prices for all held tickers
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prices: dict[str, Decimal] = {}
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for ticker in holdings:
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price = _fetch_price_with_retry(ticker, date_str)
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if price:
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prices[ticker] = price
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else:
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logger.warning(f" Could not fetch price for {TICKER_NAMES.get(ticker, ticker)} on {snap_date}")
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if not prices:
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logger.warning(f" Skipping {snap_date}: no prices available")
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continue
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# Calculate portfolio value
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total_value = Decimal("0")
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snapshot_holdings = []
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for ticker, qty in holdings.items():
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if ticker not in prices:
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continue
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value = qty * prices[ticker]
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total_value += value
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snapshot_holdings.append({
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"ticker": ticker,
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"quantity": qty,
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"price": prices[ticker],
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"value": value,
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})
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if total_value == 0:
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continue
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# Create snapshot
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snapshot = PortfolioSnapshot(
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portfolio_id=portfolio.id,
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total_value=total_value,
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snapshot_date=snap_date,
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)
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db.add(snapshot)
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db.flush()
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# Create snapshot holdings with ratios
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for h in snapshot_holdings:
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ratio = (h["value"] / total_value * 100).quantize(Decimal("0.01"), rounding=ROUND_HALF_UP)
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db.add(SnapshotHolding(
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snapshot_id=snapshot.id,
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ticker=h["ticker"],
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quantity=h["quantity"],
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price=h["price"],
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value=h["value"],
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current_ratio=ratio,
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))
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created += 1
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logger.info(f" Snapshot {snap_date}: total={total_value:,.0f}")
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# Rate limit: be gentle with KRX
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time.sleep(1)
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db.commit()
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logger.info(f"Done! Created {created} snapshots.")
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if __name__ == "__main__":
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db = SessionLocal()
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try:
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generate_snapshots(db)
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finally:
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db.close()
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