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
How do I write my own Kedro starter projects?
How can I convert functions from Jupyter Notebooks into Kedro nodes?
How do I connect a Kedro project kernel to other Jupyter clients like JupyterLab?
Can I read the same data file using two different dataset implementations?
How do I create a modular pipeline?
Can I use generator functions in a node?
Can I annotate a Kedro-Viz visualisation to show different data layers?