mldebug 0.0.2

mldebug is a lightweight Python toolkit for debugging machine learning systems in production.

mldebug

mldebug is a lightweight Python toolkit for debugging machine learning systems in production.

Quick Start

git clone https://github.com/anpenta/mldebug
cd mldebug
direnv allow
poe test

Status

Active development (v0.x, not yet stable).

Features

• Debug ML systems in production environments
• Lightweight diagnostic utilities
• Designed for integration into modern ML pipelines
• Focus on observability and failure analysis

Installation

pip install mldebug

Example Usage

See public API tests for real usage examples.

Documentation

See documentation pages.

Development Setup

Requirements

• Ubuntu 24.04.4 (recommended) or WSL
• Git
• direnv

Environment Setup

If not already done via Quick Start:

direnv allow

Development Workflow

Tasks are managed via poe (available in the project environment via direnv).

Run tests

poe test

Run linting

poe lint

Check linting

poe lint-check

Run full CI parity checks

poe test-all

poe lint-check-all

CI/CD

CI runs multi-Python version testing and linting. All pull requests must pass the checks before merging.

See CI workflow for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Ensure all CI checks pass
5. Open a pull request

Dependency Management

Dependencies are managed using uv and defined in pyproject.toml.

License

See LICENSE.