Getting Started
Introduction
Featuresmith is an open-source Python library for dataset profiling, rule-based validation, and intelligent feature analysis. This guide will get you up and running in minutes.
What is Featuresmith?
Modern data pipelines move fast. Schema drift, unexpected nulls, and silent type coercions cause downstream failures that are expensive to debug. Featuresmith gives you a lightweight, composable toolkit to understand and validate your data before it causes problems.
- Profile datasets to understand distributions, nulls, and cardinality
- Define validation rules as code, not configuration
- Run analysis from the CLI or integrate into any Python workflow
- Designed to scale from a single script to a full CI/CD pipeline
Installation
Install Featuresmith from PyPI using pip:
bash
pip install featuresmith-core featuresmith-cliRequires Python 3.11 or higher. Featuresmith uses Polars and Pandas under the hood, which are installed automatically.
Quick Start
Load a dataset and run your first profile in three lines:
quickstart.py
python
import featuresmith as fs# Load a CSV filedataset = fs.load("data.csv")# Profile your dataprofile = fs.profile(dataset)for name, col in profile.column_profiles.items(): print(f"{name}: {col.missing_count} missing values")Explore the docs
InstallationInstall Featuresmith via pip or from source.Read moreQuick StartLoad a dataset, run your first profile, and validate in minutes.Read morePython SDKFull API reference for the Dataset, Profile, and Rule classes.Read moreCLI ReferenceCommand-line interface for analyze, profile, and validate.Read more