Open Source Projects
For many years I’ve been building and maintaining open source software that helps developers work more efficiently and effectively. My projects span a range of domains including machine learning tools, data analysis libraries, development tooling, and geospatial utilities. With a focus on Python development, I’ve contributed to the scientific computing ecosystem through projects like Category Encoders (now part of scikit-learn-contrib) and created developer tools like Git Pandas for repository analysis.
Here are some of the open source projects I maintain:
PyGeoHash
A Python library for working with geohashes, providing encoding, decoding, and distance calculations.
Related Posts
- PyGeoHash Gets Type Hints: A Journey into Modern Python - Adding comprehensive type hints and a new types module
- PyGeoHash v3.0.0: Faster, Freer, and More Pythonic - Latest major release with complete rewrite
- PyGeoHash 2.1.0: Modernizing a Geospatial Python Library - Modernization and new features
- Using Cursor for Library Maintenance - How AI tools helped revitalize PyGeoHash
Keeks
A Python library for key-value store benchmarking and performance testing.
Related Posts
- Keeks 0.1.0 Release: Optimal Bankroll Management Made Simple - First major release announcement and features
- Kelly Criterion Implementation - Deep dive into the Kelly Criterion and its implementation in Keeks
- Taking Things Seriously: Holiday Edition - Early development and integration with other tools
Cookiecutter PIP Project
A modern, production-ready cookiecutter template for Python packages that follows best practices. This template sets up a complete development environment with all the tools needed to build, test, and publish professional Python libraries.
Git Pandas
A Python library that wraps GitPython to produce pandas dataframes for Git repository analysis. Enables data-driven analysis of Git repositories with features for commit history, blame information, and project-level insights.
Related Posts
- git-pandas Caching: Faster Analysis - Performance improvements through caching implementation
- Year’s End: Looking Back 2017 - Updates on Redis-based caching and professional usage
- Create organization-wide punchcards with git-pandas - New punchcard visualization features
- Gitpandas v0.0.6: python 2.7, fileowners, file-wise blame and examples - Release notes and new features
- Git-Pandas v0.0.5: coverage.py, risk, and more - Release notes and risk analysis features
- Visualize all of your git repositories with gitnoc and git-pandas - Introduction to GitNOC visualization tool
- Analyzing GitPython and Pandas With GitPandas - Early analysis and examples
Elote
A Python library implementing various rating and ranking algorithms.
Related Posts
- Elote 1.0.0 Release: Rating Systems Made Simple - Major release announcement and new features
- The Elo Rating System - Deep dive into Elo ratings with Elote
- Elote: A Python Package of Rating Systems - Original introduction to the library
Stargazers
A modern CLI tool to fetch, analyze, and summarize the stargazers or forkers of any public GitHub repository.
Related Posts
- Introducing ‘stargazers’: A Tool to Understand Your GitHub Audience - Announcing the tool and its features
Writing Tools MCP
A Model Context Protocol (MCP) server providing text analysis tools to help improve writing quality. Integrates with AI assistants like Claude to offer readability scoring, keyword analysis, and style checking.
Related Posts
- Writing Tools MCP: A Toolkit for Better Writing - Introduction and usage guide
Category Encoders
A scikit-learn-contrib library providing encoders for categorical variables as part of machine learning workflows. I authored this project but am no longer the day to day maintainer.
Related Posts
- OneHotEncoder: The Workhorse of Categorical Encoding - Deep dive into one-hot encoding implementation and best practices
- The Category Encoders Journey - Reflecting on the project’s growth and impact
- Category Encoders Published in JOSS - Academic publication milestone
- Category Encoders Accepted into scikit-learn-contrib - Major ecosystem integration
- Beyond One Hot: An Exploration of Categorical Variables - Original motivation and exploration