Maze provides an applied reinforcement learning framework for developing projects in Python.
Kedro
Kedro helps create reproducible, maintainable, and modular data science and data engineering pipelines.
About Kedro
Kedro is a Python framework for building data engineering and data science pipelines that are reproducible, maintainable and modular. It uses software engineering practices including testing with pytest, documentation with Sphinx, linting with ruff, and standard Python logging.
It provides a project template, a Data Catalog for saving and loading data across local, network, cloud object stores and HDFS with versioning for file-based systems, dependency resolution between Python functions with visualisation via Kedro-Viz, and deployment support for single, distributed, Argo, Prefect, Kubeflow, AWS Batch and Databricks setups.
Key features
- Standard project template based on Cookiecutter Data Science
- Data connectors for local, network, cloud object stores and HDFS
- Data and model versioning for file-based systems
- Automatic dependency resolution between Python functions
- Pipeline visualisation using Kedro-Viz
- Deployment support for Argo, Prefect, Kubeflow, AWS Batch, Databricks
Best for: Teams building data science and data engineering pipelines in Python who need shared structure and practices.
Good for
- Covers project structure, data handling, testing, documentation and deployment
- Works with multiple file systems including cloud object stores and HDFS
- Supports several deployment targets including Kubeflow and Databricks
Kedro at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Kedro FAQ
How do I install Kedro?
From PyPI run: uv pip install kedro. With conda run: conda install -c conda-forge kedro.
How can I learn to build a project?
Review the spaceflights tutorial to build a Kedro project for hands-on experience.
Can I use Kedro with Jupyter notebooks?
Yes, the documentation explains how to work with Kedro and Jupyter notebooks.
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