| import yfinance as yf |
| from datetime import datetime |
| from typing import Any |
|
|
|
|
| def _safe_value(data, key, default=None): |
| val = data.get(key, default) |
| return default if (val is None or val != val) else val |
|
|
|
|
| def _to_billions(value): |
| if value is None: |
| return None |
| try: |
| return round(float(value) / 1e9, 2) |
| except (TypeError, ValueError): |
| return None |
|
|
|
|
| def _format_date_yyyymmdd(value): |
| if value is None: |
| return None |
| if isinstance(value, (int, float)): |
| try: |
| return datetime.fromtimestamp(value).strftime("%Y-%m-%d") |
| except (OverflowError, OSError, ValueError): |
| return None |
| text = str(value).strip() |
| return text[:10] if text else None |
|
|
|
|
| def fetch_price_data(ticker, period="1y"): |
| stock = yf.Ticker(ticker) |
| hist = stock.history(period=period) |
| if hist.empty: |
| return {} |
| close = hist["Close"] |
| current = close.iloc[-1] |
| week_ago = close.iloc[-6] if len(close) >= 6 else close.iloc[0] |
| month_ago = close.iloc[-22] if len(close) >= 22 else close.iloc[0] |
| year_start = close.iloc[0] |
| return { |
| "current_price": round(float(current), 2), |
| "change_1w_pct": round((current / week_ago - 1) * 100, 2), |
| "change_1m_pct": round((current / month_ago - 1) * 100, 2), |
| "change_ytd_pct": round((current / year_start - 1) * 100, 2), |
| "52w_high": round(float(close.max()), 2), |
| "52w_low": round(float(close.min()), 2), |
| "avg_volume_30d": int(hist["Volume"].tail(30).mean()), |
| } |
|
|
| def fetch_fundamentals(ticker): |
| info = yf.Ticker(ticker).info or {} |
| return { |
| "company_name": _safe_value(info, "longName", ticker), |
| "symbol": _safe_value(info, "symbol", ticker), |
| "exchange": _safe_value(info, "exchange", "N/A"), |
| "quote_type": _safe_value(info, "quoteType"), |
| "currency": _safe_value(info, "currency"), |
| "sector": _safe_value(info, "sector", "N/A"), |
| "industry": _safe_value(info, "industry", "N/A"), |
| "country": _safe_value(info, "country"), |
| "city": _safe_value(info, "city"), |
| "website": _safe_value(info, "website"), |
| "full_time_employees": _safe_value(info, "fullTimeEmployees"), |
| "market_cap_b": _to_billions(_safe_value(info, "marketCap")), |
| "enterprise_value_b": _to_billions(_safe_value(info, "enterpriseValue")), |
| "shares_outstanding_b": _to_billions(_safe_value(info, "sharesOutstanding")), |
| "float_shares_b": _to_billions(_safe_value(info, "floatShares")), |
| "pe_ratio": _safe_value(info, "trailingPE"), |
| "forward_pe": _safe_value(info, "forwardPE"), |
| "pb_ratio": _safe_value(info, "priceToBook"), |
| "ps_ratio": _safe_value(info, "priceToSalesTrailing12Months"), |
| "ev_to_ebitda": _safe_value(info, "enterpriseToEbitda"), |
| "trailing_eps": _safe_value(info, "trailingEps"), |
| "forward_eps": _safe_value(info, "forwardEps"), |
| "roe": _safe_value(info, "returnOnEquity"), |
| "roa": _safe_value(info, "returnOnAssets"), |
| "gross_margin": _safe_value(info, "grossMargins"), |
| "ebitda_margin": _safe_value(info, "ebitdaMargins"), |
| "operating_margin": _safe_value(info, "operatingMargins"), |
| "profit_margin": _safe_value(info, "profitMargins"), |
| "revenue_growth": _safe_value(info, "revenueGrowth"), |
| "earnings_growth": _safe_value(info, "earningsGrowth"), |
| "debt_to_equity": _safe_value(info, "debtToEquity"), |
| "current_ratio": _safe_value(info, "currentRatio"), |
| "quick_ratio": _safe_value(info, "quickRatio"), |
| "total_cash_b": _to_billions(_safe_value(info, "totalCash")), |
| "total_debt_b": _to_billions(_safe_value(info, "totalDebt")), |
| "operating_cashflow_b": _to_billions(_safe_value(info, "operatingCashflow")), |
| "free_cashflow_b": _to_billions(_safe_value(info, "freeCashflow")), |
| "dividend_rate": _safe_value(info, "dividendRate"), |
| "dividend_yield": _safe_value(info, "dividendYield"), |
| "payout_ratio": _safe_value(info, "payoutRatio"), |
| "ex_dividend_date": _format_date_yyyymmdd(_safe_value(info, "exDividendDate")), |
| "held_percent_insiders": _safe_value(info, "heldPercentInsiders"), |
| "held_percent_institutions": _safe_value(info, "heldPercentInstitutions"), |
| "short_ratio": _safe_value(info, "shortRatio"), |
| "short_percent_float": _safe_value(info, "shortPercentOfFloat"), |
| "analyst_target": _safe_value(info, "targetMeanPrice"), |
| "target_high_price": _safe_value(info, "targetHighPrice"), |
| "target_low_price": _safe_value(info, "targetLowPrice"), |
| "analyst_opinion_count": _safe_value(info, "numberOfAnalystOpinions"), |
| "recommendation": _safe_value(info, "recommendationKey"), |
| "beta": _safe_value(info, "beta"), |
| "description": (_safe_value(info, "longBusinessSummary") or "")[:400], |
| } |
|
|
| def fetch_news(ticker, max_items=8): |
| try: |
| raw_news = yf.Ticker(ticker).news or [] |
| snippets = [] |
| for item in raw_news[:max_items]: |
| content = item.get("content", {}) |
| title = content.get("title") or item.get("title", "") |
| summary = content.get("summary") or "" |
| pub_raw = content.get("pubDate") or item.get("providerPublishTime", "") |
| pub_dt = _parse_pub_date(pub_raw) |
| if title: |
| line = f"[{pub_dt}] {title}" |
| if summary: |
| line += f" — {summary[:120]}" |
| snippets.append(line) |
| return snippets |
| except Exception as e: |
| print(f" 뉴스 수집 오류: {e}") |
| return [] |
|
|
| def _parse_pub_date(pub_raw): |
| if isinstance(pub_raw, int): |
| return datetime.fromtimestamp(pub_raw).strftime("%Y-%m-%d") |
| if isinstance(pub_raw, str) and pub_raw: |
| return pub_raw[:10] |
| return "날짜 미상" |
|
|
