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specified_field_filter

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指定字段过滤器。根据指定的字段信息进行筛选。支持对JSONL格式数据指定字段进行过滤。 本SKILL使用依赖data_juicer,请在调用前安装好python环境并安装data_juicer,你可用以下指令进行安装: pip install py-data-juicer 当用户提到字段过滤、字段值筛选、元数据过滤、指定字段过滤、按字段值过滤等需求时使用此skill。

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Source SKILL.md: https://github.com/cas-bigdatalab/piflow/blob/HEAD/workspace/skills/specified_field_filter/SKILL.md

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功能概述

该算子根据指定字段的值进行过滤,保留字段值在目标值列表中的样本。支持嵌套字段和列表字段。

核心参数

参数类型必填默认值说明
input_pathstring是-输入数据文件路径 (JSON/JSONL格式)
output_pathstring是-输出数据文件路径 (JSONL格式)
field_keystring是-字段路径,用点号分隔,如 'meta.suffix' 或 'meta.path.test'
target_valuelist是-目标值列表,如 ['.pdf', '.txt']
num_procint否1并行处理的进程数

输入数据格式

输入文件应为 JSON 或 JSONL 格式,每行包含一个样本,样本需包含指定的字段:

{"text": "文本内容", "meta": {"suffix": ".pdf", "star": 50}}

支持嵌套字段:

{"text": "文本内容", "meta": {"path": {"test": ["txt", "json"]}}}

输出数据格式

输出为 JSONL 格式,每行一个符合条件的样本,保持原始字段结构。

使用示例

命令行调用

# 根据 meta.suffix 字段过滤
python scripts/run_specified_field_filter.py \
  --input_path /path/to/input.jsonl \
  --output_path /path/to/output.jsonl \
  --field_key meta.suffix \
  --target_value .pdf \
  --target_value .txt

# 根据嵌套列表字段过滤
python scripts/run_specified_field_filter.py \
  --input_path /path/to/input.jsonl \
  --output_path /path/to/output.jsonl \
  --field_key meta.path.test \
  --target_value pdf \
  --target_value txt \
  --target_value json

参数说明

  • --input_path: 输入文件路径
  • --output_path: 输出文件路径
  • --field_key: 字段路径,支持嵌套(如 meta.suffix)
  • --target_value: 目标值,可重复指定多个值
  • --num_proc: 并行进程数,默认1

注意事项

  1. field_key 使用点号分隔多级字段(如 meta.path.test)
  2. 如果字段值是列表,则列表中所有值都必须在 target_value 中才保留
  3. 这是 NON_STATS_FILTERS,不需要计算统计信息,处理效率较高