ZhuLinsen/daily_stock_analysis · error · ValueError
文件超过 MB 限制
Error message
文件超过 {MAX_FILE_BYTES // (1024 * 1024)}MB 限制 What it means
Guard in parse_import_from_bytes: uploaded file exceeds MAX_FILE_BYTES (2MB). Enforced before any format sniffing to bound parser memory use.
Solutions
- Trim the file to only the needed columns (code, name) before import
- For CSV, strip headers/extra columns; for xlsx, save as CSV of just the code column
- Compress workflow: paste text instead (parse_import_from_text allows 100KB) or split into batches
Example fix
# before
items = parse_import_from_bytes(open('portfolio.xlsx','rb').read(), 'portfolio.xlsx') # >2MB
# after: extract just the code column to CSV first
items = parse_import_from_bytes(csv_only_bytes, 'portfolio.csv') Defensive patterns
Strategy: validation
Validate before calling
from src.services.import_parser import MAX_FILE_BYTES
if len(data) > MAX_FILE_BYTES:
raise ValueError(f'文件过大，请精简到 {MAX_FILE_BYTES // (1024*1024)}MB 以内（仅保留代码/名称列）') Type guard
def within_file_limit(b: bytes) -> bool:
return len(b) <= 2 * 1024 * 1024 Prevention
- Show a 2MB limit in the import UI file picker
- Pre-trim broker exports to the code/name columns
- For big lists, paste text (100KB) in batches or split the file
When it happens
Trigger: Uploading a CSV/XLSX import file larger than 2MB; exporting a full watchlist with names and extra columns.
Common situations: Large broker exports; xlsx with embedded formatting/images inflating size; pasting whole portfolio history instead of the code column.
Related errors
AI-assisted analysis of ZhuLinsen/daily_stock_analysis@5159bd72e8 (2026-08-15).
Data as JSON: /api/errors/ff8cd2199f5783a7.
Report an issue: GitHub.
Appendix: source
Thrown at src/services/import_parser.py:143
return result
def parse_import_from_bytes(data: bytes, filename: Optional[str] = None) -> List[Tuple[Optional[str], Optional[str], str]]:
"""
Parse file bytes (CSV/Excel) into items.
Args:
data: File content bytes.
filename: Optional filename for format detection (e.g. "a.csv", "b.xlsx").
Returns:
List of (code, name, confidence); code may be None if resolution failed.
Raises:
ValueError: On parse error or unsupported format.
"""
if len(data) > MAX_FILE_BYTES:
raise ValueError(f"文件超过 {MAX_FILE_BYTES // (1024 * 1024)}MB 限制")
ext = ""
if filename:
ext = "." + filename.rsplit(".", 1)[-1].lower() if "." in filename else ""
logger.debug(f"[ImportParser] 开始解析文件: filename={filename or '-'}, ext={ext or '-'}, bytes={len(data)}")
looks_like_zip = len(data) >= 4 and data[:4] == b"PK\x03\x04"
# Excel: .xlsx (or zip magic)
if ext == ".xlsx" or looks_like_zip:
try:
# Use header=None to avoid silently consuming the first data row as column names
# when the sheet has no header row. We detect headers the same way as the CSV path.
df = pd.read_excel(io.BytesIO(data), sheet_name=0, engine="openpyxl", header=None, dtype=str)
if df is None or df.empty:
return []
df = df.fillna("")
first_row = [str(x).strip().lower() for x in df.iloc[0].tolist()]View on GitHub (pinned to 5159bd72e8)