Kedro architecture overview

At a high level, Kedro consists of five main parts:

Kedro project

As a data pipeline developer, you will interact with a Kedro project, which consists of:

• The conf/ directory, which contains configuration for the project, such as data catalog configuration, parameters, etc.

• The src directory, which contains the source code for the project, including:

  • The pipelines directory, which contains the source code for your pipelines.

  • settings.py file contains the settings for the project, such as library component registration, custom hooks registration, etc. All the available settings are listed and explained in the project settings chapter.

  • pipeline_registry.py file defines the project pipelines, i.e. pipelines that can be run using kedro run --pipeline.

  • __main__.py file serves as the main entry point of the project in package mode.

• pyproject.toml identifies the project root by providing project metadata, including:

  • package_name: A valid Python package name for your project package

  • project_name: A human readable name for your project

  • project_version: Kedro version with which the project was generated

Kedro starter

You can use a Kedro starter to generate a Kedro project that contains boilerplate code. We maintain a set of official starters but you can also use a custom starter of your choice.

Kedro library

Kedro library consists of independent units, each responsible for one aspect of computation in a data pipeline:

• Config Loader provides utility to parse and load configuration defined in a Kedro project.

• Pipeline provides a collection of abstractions to model data pipelines.

• Runner provides an abstraction for different execution strategy of a data pipeline.

• I/O provides a collection of abstractions to handle I/O in a project, including DataCatalog and many DataSet implementations.

Kedro framework

Kedro framework serves as the interface between a Kedro project and Kedro library components. The major building blocks of the Kedro framework include:

• Session is responsible for managing the lifecycle of a Kedro run.

• Context holds the configuration and Kedro’s main functionality, and also serves as the main entry point for interactions with core library components.

• Hooks defines all hook specifications available to extend Kedro.

• CLI defines built-in Kedro CLI commands and utilities to load custom CLI commands from plugins.

Kedro extension

You can also extend Kedro behaviour in your project using a Kedro extension, which can be a custom starter, a Python library with extra hooks implementations, extra CLI commands such as Kedro-Viz or a custom library component implementation.