causallift.context package

Submodules

causallift.context.base_context module

This module provides context for Kedro project.

class causallift.context.base_context.BaseKedroContext[source]

Bases: ABC

KedroContext is the base class which holds the configuration and Kedro’s main functionality. Project-specific context class should extend this abstract class and implement the all abstract methods.

Example:

from kedro.context import KedroContext
from kedro.pipeline import Pipeline

class ProjectContext(KedroContext):
    @property
    def pipeline(self) -> Pipeline:
        return Pipeline([])

__init__()[source]

property catalog

Read-only property referring to Kedro’s DataCatalog for this context.

Return type:: DataCatalog
Returns:: DataCatalog defined in catalog.yml.

property io

Read-only alias property referring to Kedro’s DataCatalog for this context.

Return type:: DataCatalog
Returns:: DataCatalog defined in catalog.yml.

abstract property pipeline

Abstract property for Pipeline getter.

Return type:: Pipeline
Returns:: Defined pipeline.

run(tags=None, runner=None, node_names=None, from_nodes=None, to_nodes=None)[source]

Runs the pipeline with a specified runner.

Parameters:

tags (Optional[Iterable[str]]) – An optional list of node tags which should be used to filter the nodes of the Pipeline. If specified, only the nodes containing any of these tags will be run.
runner (Optional[AbstractRunner]) – An optional parameter specifying the runner that you want to run the pipeline with.
node_names (Optional[Iterable[str]]) – An optional list of node names which should be used to filter the nodes of the Pipeline. If specified, only the nodes with these names will be run.
from_nodes (Optional[Iterable[str]]) – An optional list of node names which should be used as a starting point of the new Pipeline.
to_nodes (Optional[Iterable[str]]) – An optional list of node names which should be used as an end point of the new Pipeline.

Raises:

KedroContextError – If the resulting Pipeline is empty or incorrect tags are provided.

Return type:

Dict[str, Any]

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.

exception causallift.context.base_context.KedroContextError[source]

Bases: Exception

Error occurred when loading project and running context pipeline.

causallift.context.flexible_context module

Application entry point.

class causallift.context.flexible_context.FlexibleKedroContext(runner=None, only_missing=False, **kwargs)[source]

Bases: ProjectContext2

Overwrite the default runner and only_missing option for the run.

__init__(runner=None, only_missing=False, **kwargs)[source]

run(tags=None, runner=None, node_names=None, only_missing=False)[source]

Runs the pipeline wi th a specified runner.

Parameters:

tags (Optional[Iterable[str]]) – An optional list of node tags which should be used to filter the nodes of the Pipeline. If specified, only the nodes containing any of these tags will be run.
runner (Optional[AbstractRunner]) – An optional parameter specifying the runner that you want to run the pipeline with.
node_names (Optional[Iterable[str]]) – An optional list of node names which should be used to filter the nodes of the Pipeline. If specified, only the nodes with these names will be run.
only_missing (bool) – An option to run only missing nodes.

Raises:

KedroContextError – If the resulting Pipeline is empty or incorrect tags are provided.

Return type:

Dict[str, Any]

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.

class causallift.context.flexible_context.ProjectContext[source]

Bases: BaseKedroContext

Users can override the remaining methods from the parent class here, or create new ones (e.g. as required by plugins)

property pipeline

Abstract property for Pipeline getter.

Return type:: Pipeline
Returns:: Defined pipeline.

project_name = 'CausalLift'

project_version = '0.15.0'

run(tags=None, runner=None, node_names=None, only_missing=False)[source]

Runs the pipeline wi th a specified runner.

Parameters:

tags (Optional[Iterable[str]]) – An optional list of node tags which should be used to filter the nodes of the Pipeline. If specified, only the nodes containing any of these tags will be run.
runner (Optional[AbstractRunner]) – An optional parameter specifying the runner that you want to run the pipeline with.
node_names (Optional[Iterable[str]]) – An optional list of node names which should be used to filter the nodes of the Pipeline. If specified, only the nodes with these names will be run.
only_missing (bool) – An option to run only missing nodes.

Raises:

KedroContextError – If the resulting Pipeline is empty or incorrect tags are provided.

Return type:

Dict[str, Any]

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.

class causallift.context.flexible_context.ProjectContext1[source]

Bases: ProjectContext

Allow to specify runner by string.

run(runner=None, **kwargs)[source]

Runs the pipeline wi th a specified runner.

Parameters:

tags – An optional list of node tags which should be used to filter the nodes of the Pipeline. If specified, only the nodes containing any of these tags will be run.
runner (Union[AbstractRunner, str, None]) – An optional parameter specifying the runner that you want to run the pipeline with.
node_names – An optional list of node names which should be used to filter the nodes of the Pipeline. If specified, only the nodes with these names will be run.
only_missing – An option to run only missing nodes.

Raises:

KedroContextError – If the resulting Pipeline is empty or incorrect tags are provided.

Return type:

Dict[str, Any]

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.

class causallift.context.flexible_context.ProjectContext2[source]

Bases: ProjectContext1

Keep the output datasets in the catalog.

run(**kwargs)[source]

Runs the pipeline wi th a specified runner.

Parameters:

tags – An optional list of node tags which should be used to filter the nodes of the Pipeline. If specified, only the nodes containing any of these tags will be run.
runner – An optional parameter specifying the runner that you want to run the pipeline with.
node_names – An optional list of node names which should be used to filter the nodes of the Pipeline. If specified, only the nodes with these names will be run.
only_missing – An option to run only missing nodes.

Raises:

KedroContextError – If the resulting Pipeline is empty or incorrect tags are provided.

Return type:

Dict[str, Any]

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.