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 ofKedroSession
with session dataload_context()
: InstantiateKedroContext
objectclose()
: Close the current session — although we recommend that you use the session object as a context manager, which will callclose()
automatically, as opposed to calling the method explicitlyrun()
: 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
metadata = bootstrap_project(Path.cwd())
with KedroSession.create(metadata.package_name) as session:
session.run()
You need to tell KedroSession
the package name of your Kedro project so it can load your settings, nodes and pipelines. Additionally, you can provide the following optional arguments in KedroSession.create()
:
project_path
: Path to the project root directorysave_on_close
: A boolean value to indicate whether or not to save the session to disk when it’s closedenv
: Environment for theKedroContext
extra_params
: Optional dictionary containing extra project parameters for the underlyingKedroContext
; if specified, this will update (and therefore take precedence over) parameters retrieved from the project configuration
When you want to access to the most recent session object, use the helper function get_current_session()
as follows:
from kedro.framework.session import get_current_session
session = get_current_session()
context = session.load_context()
context.catalog.load("my_data").head()