About Gators#

What is Gators?#

Gators is a high-performance machine learning preprocessing library built on top of Polars, designed to streamline your entire ML workflow from raw data to production-ready models. Leveraging Polars’ blazing-fast multi-core processing, Gators makes data preprocessing and feature engineering both faster and simpler.

Built by the PSP Data Team at PayPal, Gators solves a critical pain point: bridging the gap between Python-based model development and production deployment. With Gators, you can develop and deploy using only Python — no more reimplementing preprocessing logic in other languages for production!

Why Gators?#

The Problem#

Traditional ML workflows face a critical challenge: data preprocessing is developed in Python (pandas/sklearn) but often needs to be reimplemented in faster languages (C++, Java, Scala) for production deployment. This creates:

  • 🔴 Maintenance burden - Two codebases to maintain

  • 🔴 Bugs and inconsistencies - Different implementations can behave differently

  • 🔴 Slower development - Every change needs to be implemented twice

The Solution#

Gators solves this by combining:

  • ✅ Python-first development - Write once, deploy everywhere

  • ✅ Production-grade performance - Polars enables Rust speeds in Python

  • ✅ Unified workflow - Same code from experimentation to production

Use Cases#

Gators is perfect for:

  • Fraud Detection - Extensive feature engineering for anomaly detection

  • Risk Modeling - Create powerful predictive features

  • Customer Analytics - Transform complex customer data

  • Time Series - Rich datetime feature engineering

  • NLP Tasks - String feature extraction and encoding

  • Production ML - Deploy preprocessing pipelines without rewriting code

Key Features#

  • 🚀 Lightning Fast: Built on Polars for multi-core parallel processing

  • 🔄 Unified API: Consistent sklearn-style .fit() and .transform() interface

  • 📦 Production Ready: Deploy the same Python code from notebook to production

  • 🎯 Comprehensive: 60+ preprocessing transformers covering every use case

  • 🔗 Pipeline Support: Chain transformers seamlessly with the Pipeline class

  • 🎓 Easy to Learn: If you know sklearn, you already know Gators

Credits#

Developed by the PSP Data Team at PayPal.

Built with ⚡ by data scientists, for data scientists

Standing on the Shoulders of Giants#

“If I have seen further, it is by standing on the shoulders of giants.” — Isaac Newton

Gators builds upon the incredible work of the open-source community. We are deeply grateful to:

  • scikit-learn (scikit-learn.org) - The foundation of ML in Python, whose elegant API design inspired Gators’ transformer interface

  • feature-engine (feature-engine.trainindata.com) - A comprehensive feature engineering library that pioneered many transformer patterns also present in Gators

These projects have shaped how millions of data scientists approach machine learning, and Gators aims to carry that tradition forward with performance optimizations powered by Polars.