看股功能更新

2026-08-16 00:05:26 +08:00
parent 9cce670b74
commit fc86fe0674
28 changed files with 3823 additions and 96 deletions
--- a/backend/app/trades.py
+++ b/backend/app/trades.py
@@ -0,0 +1,329 @@
+"""交割单解析（券商导出的成交流水 → 结构化买卖记录）。
+
+支持三类导出物（按内容嗅探，不信任扩展名）：
+  - CSV/制表符文本（utf-8-sig / gbk / gb18030 自动探测）
+  - Excel .xlsx（openpyxl；很多券商导出的 .xls 实为 xlsx 或 HTML，先按魔数分流）
+  - HTML 表格（.xls 常见真身：<table><tr><td>）
+
+列名模糊匹配兼容通达信/恒生/同花顺系的命名差异；业务名称含「买入/卖出」
+才入库，银行转账、配号、利息、红利等非交易行跳过并计数。
+"""
+from __future__ import annotations
+
+import csv
+import io
+import re
+from dataclasses import dataclass, field
+from datetime import date, datetime
+
+from fastapi import HTTPException
+
+
+@dataclass
+class ParsedTrade:
+    trade_date: date
+    ts_code: str
+    code: str
+    name: str
+    direction: str  # buy | sell
+    price: float | None
+    qty: float
+    amount: float | None
+    fee: float
+    raw: dict = field(default_factory=dict)
+
+
+@dataclass
+class ParseResult:
+    trades: list[ParsedTrade] = field(default_factory=list)
+    skipped_other: int = 0  # 非证券买卖行（转账/配号/利息等）
+    skipped_bad: list[str] = field(default_factory=list)  # 解析失败样例（截断到前 5 条）
+    header_row_index: int = -1
+    columns: dict[str, str] = field(default_factory=dict)  # 逻辑列 -> 实际列名
+
+
+# ---------- 列名别名（归一化后做「包含」匹配，先命中的优先） ----------
+COLUMN_ALIASES: dict[str, list[str]] = {
+    "date": ["成交日期", "交割日期", "交收日期", "交易日期", "过户日期", "发生日期", "清算日期", "日期"],
+    "op": ["业务名称", "业务摘要", "操作", "业务类型", "交易类型", "交易类别", "摘要", "方向", "买卖标志"],
+    "code": ["证券代码", "股票代码", "产品代码", "代码"],
+    "name": ["证券名称", "股票名称", "产品名称", "名称"],
+    "qty": ["成交数量", "发生数量", "委托数量", "成交股数", "数量"],
+    "price": ["成交价格", "成交均价", "成交价", "均价", "价格"],
+    "amount": ["成交金额", "成交清算金额", "清算金额", "发生金额", "资金发生数", "金额"],
+    "fee": ["手续费", "佣金", "印花税", "过户费", "其他费", "杂费", "规费"],
+}
+# 手续费类允许多列求和（手续费+印花税+过户费…），其余逻辑列取第一命中
+_FEE_KEYS = ("手续费", "佣金", "印花税", "过户费", "其他费", "杂费", "规费")
+
+
+def _norm_header(h: str) -> str:
+    """列名归一化：去空白、去全角、去括号单位（如「成交数量(股)」）。"""
+    h = str(h).strip().replace("　", "").replace(" ", "").replace("　", "")
+    h = re.sub(r"[（(【\[].*?[)）】\]]", "", h)
+    return h
+
+
+def _match_columns(header: list[str]) -> dict[str, str]:
+    """表头 -> 逻辑列映射。返回 {逻辑列: 实际列名}；费率类列全部收集到 fee(合并名)。"""
+    out: dict[str, str] = {}
+    fee_cols: list[str] = []
+    for h in header:
+        n = _norm_header(h)
+        if not n:
+            continue
+        for key, aliases in COLUMN_ALIASES.items():
+            if key == "fee":
+                if any(a in n for a in _FEE_KEYS):
+                    fee_cols.append(h)
+                continue
+            if key in out:
+                continue
+            if any(a in n for a in aliases):
+                out[key] = h
+                break
+    # 「费用合计」列本身已含全部费用明细，取它即可，避免与手续费/印花税等列重复累加
+    total_col = next((h for h in header if "费用合计" in _norm_header(h)), None)
+    if total_col is not None:
+        out["fee"] = total_col
+    elif fee_cols:
+        out["fee"] = "\x00".join(fee_cols)  # 多列合并存储，取值时拆开求和
+    return out
+
+
+def _looks_like_header(row: list[str]) -> bool:
+    """前 10 行里找表头：≥3 个逻辑列可识别即认为是表头。"""
+    return len(_match_columns(row)) >= 3
+
+
+def _to_float(v) -> float | None:
+    """'1,234.50' / '(123.45)' / '--' / '' → float；不可解析返回 None。"""
+    if v is None:
+        return None
+    if isinstance(v, (int, float)):
+        return float(v)
+    s = str(v).strip().replace(",", "").replace("，", "")
+    if not s or s in {"--", "-", "—"}:
+        return None
+    neg = s.startswith("(") and s.endswith(")")
+    if neg:
+        s = s[1:-1]
+    try:
+        f = float(s)
+    except ValueError:
+        return None
+    return -f if neg else f
+
+
+def _to_date(v) -> date | None:
+    if isinstance(v, datetime):
+        return v.date()
+    if isinstance(v, date):
+        return v
+    if isinstance(v, (int, float)) and not isinstance(v, bool) and 30000 < v < 60000:
+        # Excel 日期序列值（1982~2064），openpyxl 读无日期格式的单元格时会给出
+        from datetime import timedelta
+        return date(1899, 12, 30) + timedelta(days=int(v))
+    s = str(v).strip()
+    m = re.search(r"(\d{4})[-/.年](\d{1,2})[-/.月](\d{1,2})", s)
+    if not m:
+        m2 = re.fullmatch(r"(\d{4})(\d{2})(\d{2})", s)
+        if not m2:
+            return None
+        m = m2
+    y, mo, d = int(m.group(1)), int(m.group(2)), int(m.group(3))
+    try:
+        return date(y, mo, d)
+    except ValueError:
+        return None
+
+
+def _to_code_suffix(code: str) -> str:
+    """6 位代码 → 交易所后缀（60/68 沪，00/30 深，4/8/92 北交所）。"""
+    if code.startswith(("60", "68", "90")):
+        return ".SH"
+    if code.startswith(("00", "30", "20")):
+        return ".SZ"
+    return ".BJ"
+
+
+def _direction(op: str) -> str | None:
+    s = str(op)
+    if "买入" in s or "buy" in s.lower() or "证券买" in s:
+        return "buy"
+    if "卖出" in s or "sell" in s.lower() or "证券卖" in s:
+        return "sell"
+    return None
+
+
+def _parse_rows(rows: list[list[object]]) -> ParseResult:
+    """已抽成二维表的行集 → ParseResult。rows[0] 应是表头（调用方已定位）。"""
+    res = ParseResult()
+    if not rows:
+        return res
+    header = [str(h) for h in rows[0]]
+    cols = _match_columns(header)
+    res.columns = {k: v for k, v in cols.items()}
+    res.header_row_index = 0
+    need = ("date", "qty")
+    if not all(k in cols for k in need) or not ("code" in cols or "name" in cols):
+        raise HTTPException(
+            status_code=422,
+            detail="识别不到交割单表头（需要 成交日期/证券代码或证券名称/成交数量 等列），"
+                   "请确认导出的是「交割单/历史成交」文件",
+        )
+    idx = {h: i for i, h in enumerate(header)}
+
+    # 无「业务名称」列的导出（如部分招商证券格式）：靠发生金额正负判方向（买入为负）。
+    # 仅当数据里确实存在负数金额才启用，避免「全正数」格式被误判。
+    def _amount_of(row: list[object]) -> float | None:
+        i = idx.get(cols["amount"])
+        return _to_float(row[i]) if i is not None and i < len(row) else None
+
+    sign_mode = "op" not in cols and "amount" in cols and any(
+        (_amount_of(row) or 0) < 0 for row in rows[1:] if any(str(c).strip() for c in row)
+    )
+
+    def cell(row: list[object], col: str):
+        i = idx.get(col)
+        return row[i] if i is not None and i < len(row) else None
+
+    for row in rows[1:]:
+        d = _to_date(cell(row, cols["date"]))
+        code = re.sub(r"\D", "", str(cell(row, cols["code"]) or "")) if "code" in cols else ""
+        raw_amount = _amount_of(row) if sign_mode else None
+        direction = (
+            _direction(str(cell(row, cols["op"]) or "")) if "op" in cols
+            else ("buy" if (raw_amount or 0) < 0 else "sell") if sign_mode
+            else None
+        )
+        name = str(cell(row, cols["name"]) or "").strip() if "name" in cols else ""
+        if d is None or (not code and not name) or direction is None:
+            # 无日期/无代码且无名称/非买卖业务（银行转账、配号、利息、红利等）
+            if any(str(c).strip() for c in row):
+                res.skipped_other += 1
+            continue
+        if len(code) > 6:
+            code = code[-6:]  # 个别导出带市场前缀（如 1:600000 / sh600000）
+        qty = abs(_to_float(cell(row, cols["qty"])) or 0)
+        if qty <= 0:
+            res.skipped_bad.append(f"{d} {code or name} 数量无效：{cell(row, cols['qty'])!r}")
+            continue
+        price = _to_float(cell(row, cols["price"])) if "price" in cols else None
+        amount = raw_amount if sign_mode else (_to_float(cell(row, cols["amount"])) if "amount" in cols else None)
+        if amount is not None:
+            amount = abs(amount)
+        fee = 0.0
+        if "fee" in cols:
+            for fc in cols["fee"].split("\x00"):
+                f = _to_float(cell(row, fc))
+                if f:
+                    fee += abs(f)
+        # 无代码列（招商式导出）：ts_code 留空，由 API 层按 name 反查 stock_basic
+        ts_code = code + _to_code_suffix(code) if code else ""
+        res.trades.append(ParsedTrade(
+            trade_date=d,
+            code=code,
+            ts_code=ts_code,
+            name=name,
+            direction=direction,
+            price=price,
+            qty=qty,
+            amount=amount,
+            fee=round(fee, 2),
+            raw={h: row[i] if i < len(row) else None for i, h in enumerate(header)},
+        ))
+    res.skipped_bad = res.skipped_bad[:5]
+    return res
+
+
+def _find_header(rows: list[list[object]]) -> int:
+    for i, row in enumerate(rows[:10]):
+        if _looks_like_header([str(c) for c in row]):
+            return i
+    return -1
+
+
+# ---------- 输入格式分流 ----------
+def _rows_from_csv(data: bytes) -> list[list[object]]:
+    """逗号/制表符分隔文本。sniff 分隔符；跳过全空行。"""
+    text = None
+    for enc in ("utf-8-sig", "gbk", "gb18030"):
+        try:
+            text = data.decode(enc)
+            break
+        except UnicodeDecodeError:
+            continue
+    if text is None:
+        raise HTTPException(status_code=422, detail="文件编码无法识别（支持 UTF-8 / GBK）")
+    sample = text[:4096]
+    delim = "\t" if sample.count("\t") > sample.count(",") else ","
+    lines = [ln for ln in text.splitlines() if ln.strip()]
+    if not lines:
+        raise HTTPException(status_code=422, detail="文件是空的")
+    return [next(csv.reader([ln], delimiter=delim)) for ln in lines]
+
+
+def _rows_from_xlsx(data: bytes) -> list[list[object]]:
+    from openpyxl import load_workbook
+
+    try:
+        wb = load_workbook(io.BytesIO(data), read_only=True, data_only=True)
+    except Exception as e:  # noqa: BLE001 - openpyxl 对损坏文件抛各种类型
+        raise HTTPException(status_code=422, detail=f"Excel 文件无法读取：{e}") from e
+    ws = wb.active
+    rows = [[c for c in row] for row in ws.iter_rows(values_only=True)]
+    wb.close()
+    return rows
+
+
+_TD_RE = re.compile(r"<t[dh][^>]*>(.*?)</t[dh]>", re.IGNORECASE | re.DOTALL)
+_TR_RE = re.compile(r"<tr[^>]*>(.*?)</tr>", re.IGNORECASE | re.DOTALL)
+
+
+def _rows_from_html(data: bytes) -> list[list[object]]:
+    """券商导出的 .xls 常是 HTML 表格。去掉标签实体后按 <tr>/<td> 切。"""
+    text = None
+    for enc in ("utf-8", "gbk", "gb18030"):
+        try:
+            text = data.decode(enc)
+            break
+        except UnicodeDecodeError:
+            continue
+    if text is None:
+        raise HTTPException(status_code=422, detail="文件编码无法识别（支持 UTF-8 / GBK）")
+    import html as html_mod
+
+    rows: list[list[object]] = []
+    for tr in _TR_RE.findall(text):
+        cells = [html_mod.unescape(re.sub(r"<[^>]+>", "", td)).strip() for td in _TD_RE.findall(tr)]
+        rows.append(cells)
+    if not rows:
+        raise HTTPException(status_code=422, detail="HTML 里没有表格数据")
+    return rows
+
+
+def parse_statement(data: bytes, filename: str) -> ParseResult:
+    """入口：按内容魔数/特征分流 → 定位表头 → 解析。"""
+    if not data:
+        raise HTTPException(status_code=422, detail="文件是空的")
+    head = data[:512].lstrip()
+    if head.startswith(b"PK"):
+        rows = _rows_from_xlsx(data)
+    elif head[:1] in (b"<",) or head.lower().startswith(b"\xef\xbb\xbf<"):
+        rows = _rows_from_html(data)
+    elif filename.lower().endswith((".xlsx", ".xls")) and not head.startswith((b"PK", b"<")):
+        # 扩展名是 Excel 但内容既非 xlsx 也非 HTML → 试试当文本
+        rows = _rows_from_csv(data)
+    else:
+        rows = _rows_from_csv(data)
+    # 去尾部全空行，定位表头（导出物常有标题行/账户信息行在前）
+    while rows and not any(str(c).strip() for c in rows[-1]):
+        rows.pop()
+    hi = _find_header(rows)
+    if hi < 0:
+        raise HTTPException(
+            status_code=422,
+            detail="找不到表头行（前 10 行内没有 成交日期/证券代码 等列名），请确认导出的是交割单",
+        )
+    return _parse_rows(rows[hi:])