fmind/mlops-python-package

Health v2 · maintenance only

Adoption not part of the score

1415 stars · 200 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python package template that provides a production-grade code base with MLOps best practices for building and deploying machine learning projects. It integrates tooling for CI/CD, testing, linting, experiment tracking, and data pipeline validation to standardize MLOps initiatives.

Use cases

• kickstart an mlops python project
• template for machine learning package with best practices
• set up ci/cd for ml pipelines
• standardize data science codebase structure
• learn mlops project layout and tooling
• bootstrap mlflow experiment tracking project
• production-ready python package for data pipelines

When to choose

• you are starting a new Python MLOps or data pipeline project and want battle-tested conventions
• you want integrated CI/CD, testing, linting, and experiment tracking out of the box
• you want a reference implementation of MLOps best practices to learn from

When to avoid

• you need a full MLOps platform rather than a code template
• your team already has established project conventions and tooling
• you need a framework with runtime orchestration features rather than a starting codebase

Facets

library · maturity active

machine-learning etl developer-tools ci-cd testing logging configuration-management deployment machine-learning data-science developer-tools python cross-platform mlops boilerplate project-template cookiecutter mlflow pandera pydantic data-pipelines best-practices template data-engineering automation docker github-actions

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