session.md

Lifecycle management with KedroSession

Overview

A KedroSession allows you to:

• Manage the lifecycle of a Kedro run
• Persist runtime parameters with corresponding session IDs
• Traceback runtime parameters, such as CLI command flags and environment variables

KedroSession decouples Kedro's library components, managed by KedroContext, and any session data (both static and dynamic data). As a result, Kedro components and plugins can access session data without the need to import the KedroContext object and library components.

The main methods and properties of KedroSession are:

• create(): Create a new instance of KedroSession with session data
• load_context(): Instantiate KedroContext object
• close(): Close the current session — although we recommend that you use the session object as a context manager, which will call close() automatically, as opposed to calling the method explicitly
• run(): Run the pipeline with the arguments provided; see Running pipelines for details

Create a session

The following code creates a KedroSession object as a context manager and runs a pipeline inside the context, with session data provided. The session automatically closes after exit:

from kedro.framework.session import KedroSession
from kedro.framework.startup import bootstrap_project
from pathlib import Path

bootstrap_project(Path.cwd())
with KedroSession.create() as session:
    session.run()

You can provide the following optional arguments in KedroSession.create():

• project_path: Path to the project root directory
• save_on_close: A boolean value to indicate whether or not to save the session to disk when it's closed
• env: Environment for the KedroContext
• extra_params: Optional dictionary containing extra project parameters for the underlying KedroContext; if specified, this will update (and therefore take precedence over) parameters retrieved from the project configuration