0.17.7

Introduction

What is Kedro?
- Learn how to use Kedro
- Assumptions

Get started

Installation prerequisites
- Virtual environments
Install Kedro
- Verify a successful installation
- Install a development version
A “Hello World” example
- Node
- Pipeline
- DataCatalog
- Runner
- Hello Kedro!
Create a new project
Iris dataset example project
Kedro starters

Tutorial

Kedro spaceflights tutorial
- Kedro project development workflow
- Optional: Git workflow
  - Create a project repository
  - Submit your changes to GitHub
Set up the spaceflights project
Set up the data
Create a pipeline
Visualise pipelines
Namespace pipelines
Set up experiment tracking
Package a project
- Add documentation to your project
- Package your project
  - Docker, Airflow and Deployment

Kedro project setup

Dependencies
Configuration
Lifecycle management with KedroSession
- Overview
- Create a session
The mini-kedro Kedro starter

Data Catalog

The Data Catalog
Kedro IO

Nodes and pipelines

Nodes
Pipelines
- How to build a pipeline
- Bad pipelines
  - Pipeline with bad nodes
  - Pipeline with circular dependencies
Modular pipelines
Micro-packaging
Run a pipeline
Slice a pipeline

Extend Kedro

Common use cases
Hooks
Custom datasets
Kedro plugins
Create a Kedro starter
- How to create a Kedro starter
- Configuration variables
  - Example Kedro starter
Dataset transformers (deprecated)
- Develop your own dataset transformer
Decorators (deprecated)

Logging

Logging
Experiment tracking
- Enable experiment tracking
- Community solutions

Development

Set up Visual Studio Code
Set up PyCharm
Kedro’s command line interface
Linting your Kedro project
Debugging

Deployment

Deployment guide
- Deployment choices
Single-machine deployment
Distributed deployment
Deployment with Argo Workflows
Deployment with Prefect
- Prerequisites
- How to run your Kedro pipeline using Prefect
  - Convert your Kedro pipeline to Prefect flow
  - Run Prefect flow
Deployment with Kubeflow Pipelines
Deployment with AWS Batch
Deployment to a Databricks cluster
How to integrate Amazon SageMaker into your Kedro pipeline
How to deploy your Kedro pipeline with AWS Step Functions
How to deploy your Kedro pipeline on Apache Airflow with Astronomer

Tools integration

Build a Kedro pipeline with PySpark
Use Kedro with IPython and Jupyter Notebooks/Lab

FAQs

Frequently asked questions
Kedro architecture overview
Kedro Principles

Resources

Images and icons
- White background
  - Icon
  - Icon with text
- Black background
  - Icon
  - Icon with text
Kedro glossary

Contribute to Kedro

Introduction
Guidelines for contributing developers
Backwards compatibility & breaking changes
- When should I make a breaking change?
- The Kedro release model
Contribute to the Kedro documentation
Join the Technical Steering Committee

API documentation

kedro

Kedro

Docs »
kedro »
kedro.extras »
kedro.extras.logging »
kedro.extras.logging.color_logger
Edit on GitHub

kedro.extras.logging.color_logger¶

Description

A logging handler class which produces coloured logs.

Classes

ColorHandler([stream, colors])

A color log handler.

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