Lifecycle management with KedroSession


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

with KedroSession.create() as session:

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