history 与 download 的返回结构：单只股票为什么也是两层列？

import yfinance as yf

# ① 单标的：单层列 + 带时区的索引
df1 = yf.Ticker("AAPL").history(period="1mo")
# shape=(22, 7)  columns=[Open, High, Low, Close, Volume, Dividends, Stock Splits]
# index=DatetimeIndex name="Date" tz=America/New_York  time=00:00:00

# ② 批量：两层列 + tz-naive 的索引
df2 = yf.download(["AAPL", "MSFT"], period="1mo", progress=False)
# shape=(22, 10) columns=('Close','AAPL'), ('Close','MSFT'), ...
# index=DatetimeIndex name="Date" tz=None
# df2.columns.nlevels == 2  ->  True

import yfinance as yf

# 1) 单标的：两种口径各取一张，用断言确认差异只在 Adj Close
t = yf.Ticker("AAPL")
raw = t.history(period="1y", auto_adjust=False)
adj = t.history(period="1y", auto_adjust=True)
assert set(raw.columns) - set(adj.columns) == {"Adj Close"}

# 2) 批量：group_by="ticker" 后按标的切，dropna 掉跨日历产生的空行
data = yf.download(["AAPL", "MSFT", "NVDA"], period="1y",
                   group_by="ticker", progress=False, threads=True)
for sym in ["AAPL", "MSFT", "NVDA"]:
    one = data[sym].dropna(how="all")
    assert one.index.is_monotonic_increasing

# 3) 落盘前的最小检查（完整 13 项见数据审计页）
def quick_check(df):
    price_cols = [c for c in ("Open", "High", "Low", "Close") if c in df]
    return {
        "rows": len(df),
        "dup_index": int(df.index.duplicated().sum()),
        "index_tz": str(getattr(df.index, "tz", None)),
        "has_adj_close": "Adj Close" in df.columns,
        "negative_price": bool((df[price_cols] < 0).any().any()),
    }