Learn about Kedro
venv
conda
pip
kedro new
conf
src
pyproject.toml
settings.py
pipeline_registry.py
Tutorial and basic Kedro usage
pipeline()
docs
kedro jupyter notebook
kedro.ipython
catalog
context
pipelines
session
%reload_kedro
%load_node
%run_viz
KedroContext
KedroSession
--params
create_default_data_set()
Runner
project_version
Kedro projects
OmegaConf
OmegaConfigLoader
ConfigLoader
TemplatedConfigLoader
catalog.yml
type
filepath
utf-8
kedro catalog rank
kedro catalog resolve
PartitionedDataset
load
fsspec
save
_describe
KedroDataCatalog
run
*args
**kwargs
describe
kedro pipeline create
SequentialRunner
ParallelRunner
kedro run
Integrations
conf/base/spark.yml
SparkSession
MemoryDataset
DataFrame
copy_mode="assign"
ThreadRunner
kedro-mlflow
Advanced usage
bootstrap_project
configure_project
click
global
project
cookiecutter
project_name
repo_name
python_package
metadata
DataCatalog
before_node_run
CONF_SOURCE
rich
virtualenv
pytest
/tests
pytest-cov
pre-commit
kedro-sagemaker
kedro-azureml
kedro-databricks
kedro-kubeflow
kedro-vertexai
Contribute to Kedro
API documentation
KedroDeprecationWarning
KedroDeprecationWarning.args
KedroDeprecationWarning.with_traceback()
KedroPythonVersionWarning
KedroPythonVersionWarning.args
KedroPythonVersionWarning.with_traceback()
AbstractConfigLoader
MissingConfigException
AbstractDataset
AbstractVersionedDataset
CachedDataset
LambdaDataset
Version
DatasetAlreadyExistsError
DatasetError
DatasetNotFoundError
load_ipython_extension()
magic_load_node()
magic_reload_kedro()
reload_kedro()
RichHandler
node()
Pipeline
Node
ModularPipelineError
run_node()
AbstractRunner
load_obj()
KedroSessionError raised by KedroSession in the case that multiple runs are attempted in one session.
KedroSessionError
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.