ZhuLinsen/daily_stock_analysis · error · ValueError

CSV 解析失败：请检查分隔符是否一致、列数是否匹配。常见原因：引号未闭合、某行列数与其他行不一致。原始错误: {e}

Error message

CSV 解析失败：请检查分隔符是否一致、列数是否匹配。常见原因：引号未闭合、某行列数与其他行不一致。原始错误: {e}

What it means

Raised when pandas.read_csv (sep=None, python engine, header=None, dtype=str) throws pd.errors.ParserError on the pasted/parsed text. This is a strict-failure branch: structurally malformed delimiter-separated data (ragged rows, unclosed quotes) rather than merely unusual delimiters, since sep=None auto-detects those.

Source

Thrown at src/services/import_parser.py:214

        df = pd.DataFrame(rows)
        first_row = [str(x).strip().lower() for x in df.iloc[0].tolist()]
        if any(c in _CODE_ALIASES or c in _NAME_ALIASES for c in first_row):
            df.columns = df.iloc[0]
            df = df.iloc[1:].reset_index(drop=True)
        return _parse_dataframe(df)

    # Try pandas for CSV-like; use dtype=str to preserve leading zeros (e.g. 00700)
    try:
        df = pd.read_csv(io.StringIO(text), sep=None, engine="python", header=None, dtype=str)
        if df is not None and not df.empty:
            df = df.fillna("")
            first_row = [str(x).strip().lower() for x in df.iloc[0].tolist()]
            if any(c in _CODE_ALIASES or c in _NAME_ALIASES for c in first_row):
                df.columns = df.iloc[0]
                df = df.iloc[1:].reset_index(drop=True)
            return _parse_dataframe(df)
    except pd.errors.ParserError as e:
        raise ValueError(
            f"CSV 解析失败：请检查分隔符是否一致、列数是否匹配。"
            f"常见原因：引号未闭合、某行列数与其他行不一致。原始错误: {e}"
        ) from e
    except Exception:
        pass

    # Fallback: plain text, split by comma/tab/space
    lines = text.strip().splitlines()
    rows = []
    for line in lines:
        line = line.strip()
        if not line:
            continue
        parts = re.split(r"[\t,;\s]+", line)
        if parts:
            rows.append(parts)
    if not rows:
        return []

View on GitHub (pinned to 5159bd72e8)

Solutions

1. Open the file and fix the malformed line quoted in the original error (row number is in the message)
2. Normalize delimiters: re-export from the source (Excel/Sheets) as clean CSV
3. If data is loose plain text (codes separated by spaces/tabs per line), simplify to one code per line — the single-column fast path handles it without pandas

Example fix

# before: 600519,'贵州"茅台   <- unclosed quote
# after:  600519,贵州茅台
#         00700,腾讯

def is_wellformed_csv(text: str) -> bool:
    import pandas as pd, io
    try:
        pd.read_csv(io.StringIO(text), sep=None, engine='python', header=None, dtype=str)
        return True
    except pd.errors.ParserError:
        return False

try:
    items = parse_import_from_bytes(data, fn)
except ValueError as e:
    if 'CSV 解析失败' in str(e):
        # fall back to the per-line loose split the parser itself uses downstream
        lines = [l.strip() for l in data.decode('utf-8', 'ignore').splitlines() if l.strip()]
        items = parse_import_from_text('\n'.join(l.split(',')[0] for l in lines))
    else:
        raise

When it happens

Trigger: A quoted field with an unclosed quote spanning lines; rows with different column counts mid-file; embedded newlines inside quotes combined with mismatched delimiters.

Common situations: Hand-edited CSV where a quote was dropped; mixed delimiter files (some comma, some tab); copy-paste from Excel引入 stray quotes.

Related errors

• 无法识别文件编码，请使用 UTF-8 或 GBK
• invalid_import_file
• efinance 获取数据失败: {failure_message}
• efinance 获取 ETF 数据失败: {failure_message}
• 未安装 Futu OpenAPI SDK；请先执行 `pip install "futu-api==10.8.6808"

AI-assisted analysis of ZhuLinsen/daily_stock_analysis@5159bd72e8 (2026-08-15). Data as JSON: /api/errors/3237ba6668f36d66. Report an issue: GitHub.