numeric_format_cleaner

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数值格式清洗工具。读取 JSONL 结构化数据，按字段规则统一单位、数值格式、范围和空值表达，输出规整后的 JSONL 和统计文件。当用户提到数值格式化、单位统一、千分位、科学计数法、空值填充、数值规整等需求时使用此skill。即使用户没有明确说出"数值格式清洗"，只要任务涉及按字段规则整理数值表达，就应该使用此skill。不负责文本去重、标点清洗、字段校验或非数值内容整理。

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Numeric Format Cleaner 数值格式清洗 Skill

功能概述

本 skill 读取 JSONL 结构化数据，按字段规则统一数值表达：单位转换、千分位格式、科学计数法、范围限制和空值填充。适用于实验记录、环境观测、统计表等需要统一数值格式的科研数据处理场景。

触发条件

当用户请求以下任务时，应使用此skill：

数值格式清洗
单位统一
千分位规整
科学计数法输出
空值填充
按字段规则整理数值

核心参数说明

必需参数

参数	说明
`--input`	输入 JSONL 文件路径
`--output`	输出 JSONL 文件路径
`--field_rules`	字段清洗规则 JSON

可选参数

参数	说明	默认值
`--conversion_rules`	单位转换规则 JSON	空字符串
`--decimal_places`	默认小数位数	`2`
`--fill_null`	空值填充值	空字符串
`--mark_cleaned`	是否标记已清洗样本	`True`
`--stats_output`	统计输出文件路径	`numeric_format_cleaner_stats.json`

输入文件格式

输入必须为 JSONL，每行一个对象，字段值可以是数值、带单位字符串或空值。

{"distance": "12.3km", "weight": "1500g"}
{"distance": "N/A", "weight": null}

使用方法

python scripts/run_numeric_format_cleaner.py \
  --input data.jsonl \
  --output cleaned.jsonl \
  --field_rules '{"distance":{"target_unit":"m","decimal_places":2}}'

python scripts/run_numeric_format_cleaner.py \
  --input data.jsonl \
  --output cleaned.jsonl \
  --field_rules '{"distance":{"target_unit":"m","decimal_places":2},"weight":{"target_unit":"kg","decimal_places":3}}' \
  --conversion_rules '{"km::m":1000,"g::kg":0.001}' \
  --stats_output stats.json

处理示例

12.345km → 10000.00m
1500g → 1.500kg
1234567.89 → 1,234,568
0.0004567 → 4.57e-04
N/A → 按 fill_null 填充

输出示例

[OK] Numeric format cleaning completed
   Total samples: 10
   Samples with changes: 10
   Total field changes: 64
   Errors: 1

环境要求

Python 3.10+
仅依赖标准库

注意事项

输入必须是 JSONL，且字段规则用 JSON 字符串传入。
fill_null 只影响空值或 null-like 值，不会改动正常数值。
只有字段规则命中的字段才会被处理。
mark_cleaned=True 时，会在输出中追加清洗标记字段。