kedro.runner.SequentialRunner

class kedro.runner.SequentialRunner(is_async=False)[source]

SequentialRunner is an AbstractRunner implementation. It can be used to run the Pipeline in a sequential manner using a topological sort of provided nodes.

Methods

create_default_data_set(ds_name)

Factory method for creating the default data set for the runner.

run(pipeline, catalog[, hook_manager, ...])

Run the Pipeline using the datasets provided by catalog and save results back to the same objects.

run_only_missing(pipeline, catalog, hook_manager)

Run only the missing outputs from the Pipeline using the datasets provided by catalog, and save results back to the same objects.
__init__(is_async=False)[source]

Instantiates the runner classs.

Parameters:

is_async (bool) – If True, the node inputs and outputs are loaded and saved asynchronously with threads. Defaults to False.

create_default_data_set(ds_name)[source]

Factory method for creating the default data set for the runner.

Parameters:

ds_name (str) – Name of the missing data set

Return type:

AbstractDataset

Returns:

An instance of an implementation of AbstractDataset to be used for all unregistered data sets.

run(pipeline, catalog, hook_manager=None, session_id=None)

Run the Pipeline using the datasets provided by catalog and save results back to the same objects.

Parameters:

  • pipeline – The Pipeline to run.

  • catalog – The DataCatalog from which to fetch data.

  • hook_manager – The PluginManager to activate hooks.

  • session_id – The id of the session.

Raises:

ValueError – Raised when Pipeline inputs cannot be satisfied.

Returns:

Any node outputs that cannot be processed by the DataCatalog. These are returned in a dictionary, where the keys are defined by the node outputs.

run_only_missing(pipeline, catalog, hook_manager)

Run only the missing outputs from the Pipeline using the datasets provided by catalog, and save results back to the same objects.

Parameters:

  • pipeline – The Pipeline to run.

  • catalog – The DataCatalog from which to fetch data.

  • hook_manager – The PluginManager to activate hooks.

Raises:

ValueError – Raised when Pipeline inputs cannot be satisfied.

Returns:

Any node outputs that cannot be processed by the DataCatalog. These are returned in a dictionary, where the keys are defined by the node outputs.