Kedro

Overview

Kedro is an open-source Python framework for building production-ready data pipelines. It enforces software engineering best practices like modularity and reproducibility to help data scientists and engineers create maintainable data workflows.

Best for

Best for
Data scientists and engineers building robust, production-grade data pipelines.

Use cases

• Building reproducible data science pipelines
• Modularizing data engineering and ML code
• Standardizing project structure for team collaboration

Notes

Kedro is an open-source Python framework for building production-ready data pipelines. It enforces software engineering best practices like modularity and reproducibility to help data scientists and engineers create maintainable data workflows.

10,867 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

• Building reproducible data science pipelines
• Modularizing data engineering and ML code
• Standardizing project structure for team collaboration

Pros

• Promotes clean, maintainable code with modular pipeline design
• Strong community support and extensive documentation
• Integrates with popular data tools (e.g., Jupyter, MLflow)

Cons

• Steep learning curve for newcomers not used to structured frameworks
• Opinionated project structure may feel rigid for small or exploratory projects
• Requires upfront investment to adopt best practices

Indexed from awesome-llmops and enriched against its public facts.