Feature Engineering Python Packages

sf-hamilton

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

feature-engine

Feature engineering and selection open-source Python library compatible with sklearn.

apache-hamilton

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

featuretools

An open source python library for automated feature engineering

upgini

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

inference-logging-client

BharatMLStack is an open-source, end-to-end machine learning infrastructure stack built at Meesho to support real-time and batch ML workloads at Bharat scale

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

autots

Automated Time Series Forecasting

sf-hamilton-sdk

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

autocarver

Automatic optimal discretization pipeline

mloda

mloda.ai - Open Data Access for AI and ML. Plugin-based. Traceable. Framework-agnostic.

tsfel

An intuitive library to extract features from time series.

mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

divik

Divisive Intelligent K-Means algorithm (DiviK) for joint feature selection and clustering of heavily multidimensional data.

desbordante

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

tusk-ml

Automated feature engineering for (almost) any dataframe

ml4t-engineer

Feature engineering, labeling, alternative bars, and leakage-safe datasets for financial ML.

sf-hamilton-ui

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

wickra-feature-store

Turn OHLCV and microstructure event streams into ML-ready feature matrices over 497 O(1) streaming indicators — deterministic across 10 languages.

gafime

GPU-Accelerated Feature Interaction Mining Engine (GAFIME) — native heterogeneous execution across Rust CPU/SIMD, CUDA, ROCm/HIP, and Metal.

spacr

spaCR Spatial phenotype analysis of CRISPR–Cas9 screens (spaCR)

aligned

The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt

nvtabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.