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random_sampler

Official

Efficient JSONL Sampling Tool

Data & Analytics#random selection#jsonl#data sampling#random sampling#data subset
Authorcas-bigdatalab
Version1.0.0
Installs0

System Documentation

What problem does it solve?

The random_sampler skill simplifies the task of sampling JSONL data, providing the ability to randomly select a subset of data with configurable count or ratio.

Core Features & Use Cases

  • Random Sampling: Perform non-parametric random sampling of JSONL files.
  • Count-Based Sampling: Select a specified number of samples.
  • Ratio-Based Sampling: Select a percentage of samples.
  • Use Case: Useful for creating random test datasets from large JSONL files for validation and training machine learning models.

Quick Start

Use the random_sampler skill with --method count --count 50 --seed 123 to randomly select 50 records from a JSONL file with a random seed of 123.

Dependency Matrix

Required Modules

None required

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: random_sampler
Download link: https://github.com/cas-bigdatalab/piflow/archive/main.zip#random-sampler

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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