kedro.context.KedroContext¶
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class
kedro.context.
KedroContext
(project_path, env=None)[source]¶ Bases:
abc.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.-
CONF_ROOT
¶ Name of root directory containing project configuration.
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Default name is "conf".
Example:
from kedro.context import KedroContext from kedro.pipeline import Pipeline class ProjectContext(KedroContext): @property def pipeline(self) -> Pipeline: return Pipeline([])
Attributes
KedroContext.CONF_ROOT
KedroContext.catalog
Read-only property referring to Kedro’s DataCatalog
for this context.KedroContext.config_loader
Read-only property referring to Kedro’s ConfigLoader
for this context.KedroContext.io
Read-only alias property referring to Kedro’s DataCatalog
for this context.KedroContext.pipeline
Abstract property for Pipeline getter. KedroContext.project_name
Abstract property for Kedro project name. KedroContext.project_path
Read-only property containing Kedro’s root project directory. KedroContext.project_version
Abstract property for Kedro version. Methods
KedroContext.__init__
(project_path[, env])Create a context object by providing the root of a Kedro project and the environment configuration subfolders (see kedro.config.ConfigLoader
)KedroContext.run
([tags, runner, node_names, …])Runs the pipeline with a specified runner. -
CONF_ROOT
= 'conf'
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__init__
(project_path, env=None)[source]¶ Create a context object by providing the root of a Kedro project and the environment configuration subfolders (see
kedro.config.ConfigLoader
)Raises: KedroContextError
– If there is a mismatch between Kedro project version and package version.Parameters: - project_path (
Union
[Path
,str
]) – Project path to define the context for. - env (
Optional
[str
]) – Optional argument for configuration default environment to be used - running the pipeline. If not specified, it defaults to "local". (for) –
- project_path (
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catalog
¶ Read-only property referring to Kedro’s
DataCatalog
for this context.Return type: DataCatalog
Returns: DataCatalog defined in catalog.yml.
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config_loader
¶ Read-only property referring to Kedro’s
ConfigLoader
for this context.Return type: ConfigLoader
Returns: Instance of ConfigLoader created by _create_config_loader().
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io
¶ Read-only alias property referring to Kedro’s
DataCatalog
for this context.Return type: DataCatalog
Returns: DataCatalog defined in catalog.yml.
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pipeline
¶ Abstract property for Pipeline getter.
Return type: Pipeline
Returns: Defined pipeline.
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project_name
¶ Abstract property for Kedro project name.
Return type: str
Returns: Name of Kedro project.
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project_path
¶ Read-only property containing Kedro’s root project directory.
Return type: Path
Returns: Project directory.
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project_version
¶ Abstract property for Kedro version.
Return type: str
Returns: Kedro version.
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run
(tags=None, runner=None, node_names=None, from_nodes=None, to_nodes=None, pipeline=None, catalog=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 thePipeline
. 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 thePipeline
. 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 newPipeline
. - to_nodes (
Optional
[Iterable
[str
]]) – An optional list of node names which should be used as an end point of the newPipeline
. - pipeline (
Optional
[Pipeline
]) – Optional Pipeline to run, defaults to self.pipeline. - catalog (
Optional
[DataCatalog
]) – Optional DataCatalog to run with, defaults to self.catalog.
Raises: KedroContextError
– If the resultingPipeline
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.- tags (
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