Introduction
First steps
conda
pip
pandas-iris
conf
conf/base
conf/local
data
src
Next steps: Tutorial
pipeline()
Visualisation with Kedro-Viz
Notebooks & IPython users
catalog
context
pipelines
session
%reload_kedro
%run_viz
Kedro project setup
KedroSession
Data Catalog
*_args
project
GCSFileSystem
utf-8
version
IncrementalDataSet
Nodes and pipelines
**kwargs
kedro pipeline create
fsspec
SequentialRunner
ParallelRunner
kedro run
Extend Kedro
_load
_save
_describe
PartitionedDataSet
click
global
Hooks
before_node_run
Logging
Development
venv
virtualenv
pytest
/tests
pytest-cov
pre-commit
Deployment
DataCatalog
kedro airflow
PySpark integration
conf/base/spark.yml
SparkSession
MemoryDataSet
DataFrame
copy_mode="assign"
ThreadRunner
Resources
KedroContext
Contribute to Kedro
core
extras
make databricks-build
API documentation
kedro
kedro.config
kedro.datasets
kedro.extras
kedro.extras.datasets
kedro.extras.extensions
kedro.extras.extensions.ipython
kedro.extras.logging
kedro.extras.logging.color_logger
kedro.framework
kedro.framework.cli
kedro.framework.cli.catalog
kedro.framework.cli.cli
kedro.framework.cli.hooks
kedro.framework.cli.hooks.manager
kedro.framework.cli.hooks.markers
kedro.framework.cli.hooks.specs
kedro.framework.cli.jupyter
kedro.framework.cli.micropkg
kedro.framework.cli.pipeline
kedro.framework.cli.project
kedro.framework.cli.registry
kedro.framework.cli.starters
kedro.framework.cli.utils
kedro.framework.context
kedro.framework.hooks
kedro.framework.hooks.manager
kedro.framework.hooks.markers
kedro.framework.hooks.specs
kedro.framework.project
kedro.framework.session
kedro.framework.session.session
kedro.framework.session.shelvestore
kedro.framework.session.store
kedro.framework.startup
kedro.io
kedro.ipython
kedro.pipeline
kedro.runner
kedro.utils