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v0.1.0
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  • Configuration

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DocsGuide

Getting Started

  • Introduction
  • Installation
  • Quick Start
  • Benchmarks
  • Development Setup
  • Contributing

Core Concepts

  • Architecture Overview
  • Dataset Layer
  • Connectors
  • Profiling Engine
  • Rule Engine

Python SDK

  • load()
  • profile()
  • analyze()
  • Data Models
  • Exceptions
  • Plugins

CLI Reference

  • analyze
  • Configuration

Guides

  • CI/CD Integration
  • Custom Rules
  • Writing Plugins

Resources

  • Release Notes
  • FAQ
  • Troubleshooting
HomeDocsConfiguration

CLI Reference

Configuration

Configuring the Rule Engine via CLI flags and SDK arguments

Featuresmith v0.1.0 supports programmatic rule configurations in the Python SDK and command-line flags in the CLI. File-based configuration is not yet active.

Roadmap Notice: File-Based Config (.featuresmith.yml)

Layered file-based configuration (via a .featuresmith.yml file at the project root) is a planned enhancement scheduled for Phase 2+. In the current release, configure rules directly in code or use CLI flags.

1. Python SDK Configuration

Configure rules programmatically by passing the enabled_rules list and the rule_config dictionary to the fs.analyze() function:

python
1import featuresmith as fs
2
3result = fs.analyze(
4 "dataset.csv",
5 target_column="churn",
6 enabled_rules=[
7 "quality.missing_value_threshold",
8 "statistical.high_correlation"
9 ],
10 rule_config={
11 "quality.missing_value_threshold": {"threshold": 15.0},
12 "statistical.high_correlation": {"threshold": 0.85}
13 }
14)

2. CLI Options

Control CLI analyze parameters using flags (such as filtering by severity or limiting correlation analysis sizes):

bash
1# Target column and correlation column limits
2featuresmith analyze dataset.csv --target churn --max-correlation-columns 50
3
4# Severity filtering and report generation
5featuresmith analyze dataset.csv --severity warning --output report.txt

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