cas-bigdatalab/piflow/data-splitter

Claude Code and agent skill by cas-bigdatalab/piflow

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'JSONL比例切分工具。读取JSONL数据集，按给定比例拆成多个子集，支持随机切分和按字段分层切分。

Install

npx vskill@latest install cas-bigdatalab/piflow/data-splitter

SKILL.md

The same SKILL.md was published earlier as majiayu000/claude-skill-registry/data-splitter.

Data Splitter 数据分割 Skill

功能概述

本skill用于将JSONL数据集按比例拆分为多个子集，支持：

  • 随机切分：打乱后按比例拆分
  • 分层切分：按指定字段保持类别分布一致

触发条件

当用户请求以下任务时，应使用此skill：

  • 按比例拆分JSONL
  • 训练集/验证集/测试集拆分
  • 数据集切分
  • 分层切分
  • JSONL样本拆分

核心参数说明

必需参数
参数说明
--input输入JSONL文件路径
--outputs输出文件路径，逗号分隔
--ratios分割比例，逗号分隔
可选参数
参数说明默认值
--stratify_field分层字段空
--seed随机种子42
--log_file日志文件路径空

输入文件格式

jsonl
{"id": 1, "category": "A", "text": "样本1"}
{"id": 2, "category": "A", "text": "样本2"}
{"id": 3, "category": "B", "text": "样本3"}
{"id": 4, "category": "C", "text": "样本4"}

使用方法

随机切分
bash
python scripts/run_data_splitter.py \
  --input data.jsonl \
  --outputs train.jsonl,valid.jsonl,test.jsonl \
  --ratios 0.7,0.2,0.1 \
  --seed 42
分层切分
bash
python scripts/run_data_splitter.py \
  --input data.jsonl \
  --outputs train.jsonl,valid.jsonl,test.jsonl \
  --ratios 0.7,0.2,0.1 \
  --stratify_field category \
  --seed 42

输出示例

text
[OK] Data splitting completed
   [train.jsonl] 7 records (70.0%)
   [valid.jsonl] 2 records (20.0%)
   [test.jsonl] 1 records (10.0%)
   Input: data.jsonl
   Total records: 10
   Split ratios: [0.7, 0.2, 0.1]
   Stratified: True
   Stratify field: category
   Random seed: 42

环境要求

bash
python scripts/run_data_splitter.py --help

注意事项

  1. --outputs 的数量必须与 --ratios 一致。
  2. --ratios 的总和建议为 1.0。
  3. 分层切分适合类别不平衡数据，但小样本类别仍可能受整数取整影响。
  4. 输入必须是 JSONL，每行一个 JSON 对象。

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