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新增大 Excel 轻量级解析路径，解决大表格 OOM

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#53 3 comments 0 reactions 0 assignees View on GitHub

@ving7176 is already working on this.

Since Aug 18, 2026.

  • #54 by @ving7176 — open

Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
48/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Quiet
Tech stack
python
Domain
data, performance

Research direction

Start by locating load_workbook() and _find_true_data_bounds, then trace how merged ranges affect the worksheet bounds and cell creation. Reproduce the large-sheet case described in the issue and compare the existing path with the proposed SAX streaming path. Done means large Excel files can be parsed without the current 12GB+ memory failure and with the stated lower peak usage.

Written by the indexing model from the issue text.

Description

描述
处理超大 Excel（如 33MB XML sheet、74 万单元格）时，openpyxl 全量加载创建百万级 Cell 对象，内存占用超过 12GB，进程被 OOM 杀死。本 PR 新增轻量级解析路径（SAX 流式解析），内存峰值从 12GB+ 降至 2.2GB。
根因
load_workbook() 为每个单元格（含空位）创建 Cell 对象 -> 百万级对象 -> 12GB
异常文件含 18 万行合并区域（18.6 万个），拉大洪水填充边界
_find_true_data_bounds 将合并区域纳入边界，max_row=186365，洪水填充遍历 74 万空单元格

Dominant language
Python
Stars
233
Forks
41
No merged PRs in 30d

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