63e7a2ba32
- stock_tracker.py now uses yfinance for real prices - get_market_indices(): KOSPI, S&P 500, NASDAQ, DOW - get_crypto_price(): BTC, ETH, SOL with 52W range - CLI commands: 'python stock_tracker.py market' and 'crypto' Features: - Live prices from Yahoo Finance - Market indices tracking - Cryptocurrency prices - 52-week high/low - Daily change percentage Example usage: python stock_tracker.py market # Show indices python stock_tracker.py crypto --symbol BTC # BTC price
505 lines
18 KiB
Python
505 lines
18 KiB
Python
#!/usr/bin/env python3
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"""
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Stock & Crypto Portfolio Tracker
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Features:
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- Track stocks and crypto prices
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- Calculate portfolio P&L
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- Compare against market indices
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- Generate investment recommendations based on guidelines
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- Daily/weekly reports
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"""
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import os
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import json
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import datetime
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from dataclasses import dataclass, field, asdict
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from typing import List, Dict, Optional, Tuple
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from enum import Enum
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import requests
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# Try import yfinance for real market data
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try:
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import yfinance as yf
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YFINANCE_AVAILABLE = True
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except ImportError:
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YFINANCE_AVAILABLE = False
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print("⚠️ yfinance not installed. Run: pip install yfinance")
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# Configuration
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DATA_DIR = os.environ.get('PORTFOLIO_DATA_DIR', '/tmp/portfolio')
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os.makedirs(DATA_DIR, exist_ok=True)
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PORTFOLIO_FILE = os.path.join(DATA_DIR, 'portfolio.json')
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PRICES_FILE = os.path.join(DATA_DIR, 'prices.json')
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PERFORMANCE_FILE = os.path.join(DATA_DIR, 'performance.json')
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# Market API (placeholder - would use real API)
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YAHOO_API = "https://query1.finance.yahoo.com/v8/finance/chart/{symbol}"
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KRX_API = "https://api.ksicore.net/v1/stock/quote"
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class AssetType(Enum):
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STOCK = "stock"
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CRYPTO = "crypto"
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ETF = "etf"
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@dataclass
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class Position:
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symbol: str
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asset_type: str
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quantity: float
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avg_cost: float
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entry_date: str = ""
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notes: str = ""
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@dataclass
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class PriceData:
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symbol: str
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current_price: float
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change_percent: float
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high_52w: float = 0
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low_52w: float = 0
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volume: float = 0
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updated_at: str = ""
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@dataclass
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class PortfolioSummary:
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total_value: float
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total_cost: float
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total_pnl: float
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total_pnl_percent: float
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positions: List[Dict]
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top_performer: Optional[Dict]
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worst_performer: Optional[Dict]
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market_comparison: Dict = field(default_factory=dict)
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class StockTracker:
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"""Stock & Crypto Portfolio Tracker"""
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def __init__(self):
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self.positions = self._load_positions()
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self.prices = self._load_prices()
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# ============== Data Management ==============
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def _load_positions(self) -> Dict[str, Position]:
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if os.path.exists(PORTFOLIO_FILE):
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with open(PORTFOLIO_FILE, 'r') as f:
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data = json.load(f)
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return {k: Position(**v) for k, v in data.items()}
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return {}
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def _save_positions(self):
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with open(PORTFOLIO_FILE, 'w') as f:
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json.dump({k: asdict(v) for k, v in self.positions.items()}, f, indent=2)
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def _load_prices(self) -> Dict[str, PriceData]:
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if os.path.exists(PRICES_FILE):
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with open(PRICES_FILE, 'r') as f:
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return {k: PriceData(**v) for k, v in json.load(f).items()}
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return {}
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def _save_prices(self):
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with open(PRICES_FILE, 'w') as f:
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json.dump({k: asdict(v) for k, v in self.prices.items()}, f, indent=2)
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# ============== Portfolio Management ==============
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def add_position(self, symbol: str, asset_type: str, quantity: float,
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avg_cost: float, entry_date: str = "", notes: str = "") -> bool:
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"""Add a new position to portfolio"""
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try:
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key = f"{asset_type}_{symbol.upper()}"
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self.positions[key] = Position(
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symbol=symbol.upper(),
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asset_type=asset_type,
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quantity=quantity,
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avg_cost=avg_cost,
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entry_date=entry_date or datetime.datetime.now().strftime('%Y-%m-%d'),
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notes=notes
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)
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self._save_positions()
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return True
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except Exception as e:
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print(f"Error adding position: {e}")
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return False
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def remove_position(self, symbol: str, asset_type: str) -> bool:
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"""Remove a position from portfolio"""
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key = f"{asset_type}_{symbol.upper()}"
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if key in self.positions:
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del self.positions[key]
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self._save_positions()
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return True
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return False
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def get_positions(self) -> List[Position]:
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return list(self.positions.values())
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# ============== Price Fetching ==============
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def fetch_price(self, symbol: str) -> Optional[PriceData]:
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"""Fetch current price for a symbol using yfinance"""
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if YFINANCE_AVAILABLE:
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try:
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# Add .KS for Korean stocks, normal for others
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ticker = yf.Ticker(symbol)
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info = ticker.info
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current_price = info.get('currentPrice', info.get('regularMarketPrice', 0))
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change_percent = info.get('regularMarketChangePercent', 0) * 100
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high_52w = info.get('fiftyTwoWeekHigh', 0)
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low_52w = info.get('fiftyTwoWeekLow', 0)
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volume = info.get('volume', 0)
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return PriceData(
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symbol=symbol,
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current_price=current_price,
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change_percent=change_percent,
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high_52w=high_52w,
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low_52w=low_52w,
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volume=volume,
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updated_at=datetime.datetime.now().isoformat()
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)
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except Exception as e:
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print(f"Error fetching {symbol}: {e}")
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return None
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else:
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# Fallback to mock data if yfinance not available
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import random
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mock_price = random.uniform(10000, 500000)
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mock_change = random.uniform(-5, 5)
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return PriceData(
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symbol=symbol,
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current_price=mock_price,
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change_percent=mock_change,
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high_52w=mock_price * 1.2,
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low_52w=mock_price * 0.8,
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volume=random.uniform(100000, 10000000),
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updated_at=datetime.datetime.now().isoformat()
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)
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def update_prices(self) -> Dict[str, PriceData]:
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"""Update all prices"""
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for key, pos in self.positions.items():
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price = self.fetch_price(pos.symbol)
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if price:
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self.prices[key] = price
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self._save_prices()
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return self.prices
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# ============== Performance Calculation ==============
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def calculate_portfolio_summary(self) -> PortfolioSummary:
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"""Calculate portfolio summary with P&L"""
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total_value = 0
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total_cost = 0
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positions_data = []
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for key, pos in self.positions.items():
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price = self.prices.get(key)
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if price:
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current_value = pos.quantity * price.current_price
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cost_basis = pos.quantity * pos.avg_cost
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pnl = current_value - cost_basis
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pnl_percent = (pnl / cost_basis) * 100 if cost_basis > 0 else 0
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positions_data.append({
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'symbol': pos.symbol,
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'type': pos.asset_type,
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'quantity': pos.quantity,
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'avg_cost': pos.avg_cost,
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'current_price': price.current_price,
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'current_value': current_value,
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'cost_basis': cost_basis,
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'pnl': pnl,
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'pnl_percent': pnl_percent,
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'change_24h': price.change_percent,
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'52w_high': price.high_52w,
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'52w_low': price.low_52w,
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})
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total_value += current_value
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total_cost += cost_basis
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total_pnl = total_value - total_cost
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total_pnl_percent = (total_pnl / total_cost) * 100 if total_cost > 0 else 0
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# Top/Worst performers
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sorted_positions = sorted(positions_data, key=lambda x: x['pnl_percent'], reverse=True)
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top_performer = sorted_positions[0] if sorted_positions else None
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worst_performer = sorted_positions[-1] if sorted_positions else None
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return PortfolioSummary(
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total_value=total_value,
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total_cost=total_cost,
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total_pnl=total_pnl,
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total_pnl_percent=total_pnl_percent,
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positions=positions_data,
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top_performer=top_performer,
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worst_performer=worst_performer
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)
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# ============== Investment Recommendations ==============
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def check_investment_guidelines(self, symbol: str) -> Dict:
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"""
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Check if a stock meets investment guidelines
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Reference: 주식 투자 원칙 가이드.md
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"""
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# Placeholder - would fetch real data
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return {
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'symbol': symbol,
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'pbr': None, # Would fetch from data source
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'roe': None,
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'per': None,
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'score': None,
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'recommendation': None,
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'checklist': {
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'story_clear': False,
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'earnings_uptrend': False,
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'balance_sheet_healthy': False,
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'capital_return_plan': False,
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'governance_clean': False,
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'market_liquidity': False,
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'relative_strength': False,
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}
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}
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def get_recommendation(self) -> List[Dict]:
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"""Generate investment recommendations based on guidelines"""
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# Filter positions that meet criteria
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recommendations = []
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for key, pos in self.positions.items():
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if pos.asset_type == 'stock':
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analysis = self.check_investment_guidelines(pos.symbol)
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recommendations.append({
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'symbol': pos.symbol,
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'action': 'HOLD',
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'reason': 'Review weekly',
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'checklist_score': f"{sum(analysis['checklist'].values())}/7",
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'pnl_percent': self._get_position_pnl(key)
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})
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return recommendations
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def _get_position_pnl(self, key: str) -> float:
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pos = self.positions.get(key)
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price = self.prices.get(key)
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if pos and price:
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return ((price.current_price - pos.avg_cost) / pos.avg_cost) * 100
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return 0
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# ============== Crypto & Market Data ==============
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def get_crypto_price(self, symbol: str = "BTC") -> Optional[PriceData]:
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"""Fetch cryptocurrency price using yfinance"""
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if not YFINANCE_AVAILABLE:
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return None
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try:
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ticker = yf.Ticker(f"{symbol}-USD")
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hist = ticker.history(period='1d')
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hist_1d = ticker.history(period='2d') # Get 2 days for change
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if hist.empty:
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return None
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current_price = hist['Close'].iloc[-1]
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prev_close = hist_1d['Close'].iloc[0] if len(hist_1d) > 1 else current_price
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change_percent = ((current_price - prev_close) / prev_close) * 100 if prev_close > 0 else 0
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# Get 52-week data
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hist_52w = ticker.history(period='1y')
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high_52w = hist_52w['High'].max() if not hist_52w.empty else current_price * 1.2
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low_52w = hist_52w['Low'].min() if not hist_52w.empty else current_price * 0.8
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return PriceData(
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symbol=symbol,
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current_price=current_price,
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change_percent=change_percent,
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high_52w=high_52w,
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low_52w=low_52w,
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volume=hist['Volume'].iloc[-1] if 'Volume' in hist.columns else 0,
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updated_at=datetime.datetime.now().isoformat()
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)
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except Exception as e:
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print(f"Error fetching crypto {symbol}: {e}")
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return None
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def get_market_indices(self) -> Dict[str, Dict]:
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"""Fetch major market indices using yfinance"""
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indices = {
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'KOSPI': '^KS11',
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'KOSDAQ': '^KOSDAQ',
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'S&P 500': '^GSPC',
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'NASDAQ': '^IXIC',
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'DOW': '^DJI'
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}
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result = {}
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if YFINANCE_AVAILABLE:
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for name, ticker in indices.items():
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try:
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t = yf.Ticker(ticker)
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hist = t.history(period='1d')
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hist_1d = t.history(period='2d') # Get 2 days for change calculation
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if not hist.empty:
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current = hist['Close'].iloc[-1]
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prev_close = hist_1d['Close'].iloc[0] if len(hist_1d) > 1 else current
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change = ((current - prev_close) / prev_close) * 100 if prev_close > 0 else 0
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result[name] = {'price': current, 'change': change}
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else:
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result[name] = {'price': 0, 'change': 0}
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except Exception as e:
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print(f"Error fetching {name}: {e}")
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result[name] = {'price': 0, 'change': 0}
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return result
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# ============== Reporting ==============
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def generate_daily_report(self) -> str:
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"""Generate daily portfolio report"""
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summary = self.calculate_portfolio_summary()
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report = f"""
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📊 **일일 포트폴리오 리포트**
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**Date:** {datetime.datetime.now().strftime('%Y-%m-%d')}
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💰 **전체 현황**
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- 현재 가치: ₩{summary.total_value:,.0f}
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- 투자 원금: ₩{summary.total_cost:,.0f}
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- 총 손익: ₩{summary.total_pnl:,.0f} ({summary.total_pnl_percent:+.1f}%)
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📈 **상위 수익**
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"""
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for pos in sorted(summary.positions, key=lambda x: x['pnl_percent'], reverse=True)[:3]:
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emoji = "🟢" if pos['pnl_percent'] > 0 else "🔴"
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report += f"- {emoji} **{pos['symbol']}**: {pos['pnl_percent']:+.1f}% (₩{pos['pnl']:,.0f})\n"
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report += "\n💡 **투자 원칙 체크**\n"
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report += "- ⬜ 3년 실적 우상향 확인\n"
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report += "- ⬜ PBR < 1 확인\n"
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report += "- ⬜ 추적 손절 –10% 설정\n"
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report += "- ⬜ 주 1회 점검 예정\n"
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return report
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def generate_weekly_report(self) -> str:
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"""Generate weekly portfolio report"""
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summary = self.calculate_portfolio_summary()
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report = f"""
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📈 **주간 포트폴리오 리포트**
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**Week:** {datetime.datetime.now().strftime('%Y-%W')}
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🎯 **이번 주 목표**
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- [ ] 시장·섹터 상대강도 Top/Bottom 5 확인
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- [ ] 관찰목록 체크리스트 재적용
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- [ ] 엔트리·손절·추적손절 가격 기입
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- [ ] 트레이드 로그 작성
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💰 **포트폴리오 현황**
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| 항목 | 수치 |
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|------|------|
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| 총 가치 | ₩{summary.total_value:,.0f} |
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| 총 수익률 | {summary.total_pnl_percent:+.1f}% |
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| 베스트 | {summary.top_performer['symbol'] if summary.top_performer else 'N/A'} ({summary.top_performer['pnl_percent'] if summary.top_performer else 0:+.1f}%) |
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| 워스트 | {summary.worst_performer['symbol'] if summary.worst_performer else 'N/A'} ({summary.worst_performer['pnl_percent'] if summary.worst_performer else 0:+.1f}%) |
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📋 **체크리스트 이행**
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- [ ] 가치 > 가격 확인
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- [ ] –10% 손절 규칙 적용
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- [ ] 핵심 2~5종목 집중 확인
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"""
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return report
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# ============== CLI Interface ==============
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def main():
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import argparse
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parser = argparse.ArgumentParser(description='Stock & Crypto Portfolio Tracker')
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subparsers = parser.add_subparsers(dest='command', help='Available commands')
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# Add position
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add_parser = subparsers.add_parser('add', help='Add a position')
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add_parser.add_argument('--symbol', required=True)
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add_parser.add_argument('--type', required=True, choices=['stock', 'crypto', 'etf'])
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add_parser.add_argument('--quantity', type=float, required=True)
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add_parser.add_argument('--cost', type=float, required=True)
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# Show portfolio
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subparsers.add_parser('show', help='Show portfolio summary')
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# Update prices
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subparsers.add_parser('update', help='Update prices from market')
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# Daily report
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subparsers.add_parser('daily', help='Generate daily report')
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# Weekly report
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subparsers.add_parser('weekly', help='Generate weekly report')
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# Crypto price
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crypto_parser = subparsers.add_parser('crypto', help='Get crypto price')
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crypto_parser.add_argument('--symbol', default='BTC', help='Crypto symbol (BTC, ETH, etc.)')
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# Market indices
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subparsers.add_parser('market', help='Show market indices')
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args = parser.parse_args()
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tracker = StockTracker()
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if args.command == 'add':
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tracker.add_position(args.symbol, args.type, args.quantity, args.cost)
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print(f"✅ Added {args.quantity} {args.symbol} @ ₩{args.cost}")
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elif args.command == 'show':
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summary = tracker.calculate_portfolio_summary()
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print(f"\n📊 Portfolio Summary")
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print(f"Total Value: ₩{summary.total_value:,.0f}")
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print(f"Total Cost: ₩{summary.total_cost:,.0f}")
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print(f"P&L: ₩{summary.total_pnl:,.0f} ({summary.total_pnl_percent:+.1f}%)")
|
||
print(f"\nPositions ({len(summary.positions)}):")
|
||
for pos in summary.positions:
|
||
print(f" {pos['symbol']}: {pos['quantity']} @ ₩{pos['avg_cost']:,.0f} → ₩{pos['current_price']:,.0f} ({pos['pnl_percent']:+.1f}%)")
|
||
|
||
elif args.command == 'update':
|
||
prices = tracker.update_prices()
|
||
print(f"✅ Updated {len(prices)} prices")
|
||
|
||
elif args.command == 'daily':
|
||
print(tracker.generate_daily_report())
|
||
|
||
elif args.command == 'weekly':
|
||
print(tracker.generate_weekly_report())
|
||
|
||
elif args.command == 'crypto':
|
||
price = tracker.get_crypto_price(args.symbol)
|
||
if price:
|
||
emoji = "🟢" if price.change_percent > 0 else "🔴"
|
||
print(f"\n{emoji} {args.symbol}: ${price.current_price:,.2f} ({price.change_percent:+.2f}%)")
|
||
print(f" 52W Range: ${price.low_52w:,.2f} - ${price.high_52w:,.2f}")
|
||
else:
|
||
print("❌ yfinance not available. Install: pip install yfinance")
|
||
|
||
elif args.command == 'market':
|
||
indices = tracker.get_market_indices()
|
||
print("\n📈 Market Indices")
|
||
for name, data in indices.items():
|
||
emoji = "🟢" if data['change'] > 0 else "🔴"
|
||
print(f" {emoji} {name}: {data['price']:,.2f} ({data['change']:+.2f}%)")
|
||
|
||
else:
|
||
parser.print_help()
|
||
|
||
if __name__ == '__main__':
|
||
main()
|