Guide to CLI commands¶
Note: This documentation is based on
Kedro 0.16.2, if you spot anything that is incorrect then please create an issue or pull request.
kedro command line interface (CLI) helps with reproducibility in projects by allowing you to associate a set of commands and dependencies with a target and then execute them from the command line when inside a Kedro project directory. All project related CLI commands should be run from the project’s root directory.
The supported commands are specified in the
kedro_cli.py file. It is easy to extend
kedro_cli.py by either modifying the file or injecting commands into it by using the plugin framework.
To allow your shell to autocomplete
kedro commands, you can add the following to your
.bashrc (or just run it on the command line)
eval "$(_KEDRO_COMPLETE=source kedro)"
Global Kedro commands¶
Show version and exit:
kedro -V kedro --version
See extensive logging and error stack traces:
kedro -v kedro --verbose
Get help on Kedro commands:
kedro -h kedro --help
Create a new kedro project:
See the Kedro API documentation (including the tutorial):
Project-specific Kedro commands¶
run() method of the
ProjectContext defined in
To make sure the project is shareable and reproducible, you should maintain the
kedro run program definitions in the
kedro_cli.py to point to the entry point in your project.
Build the project dependency requirements. This command will run
src/requirements.in file. If the file doesn’t exist, Kedro will create it by copying the contents from
kedro build-reqs also accepts and passes through CLI options accepted by
pip-compile. For example,
kedro build-reqs --generate-hashes will call
pip-compile --generate-hashes src/requirements.in.
Install all package dependencies specified in
kedro install will also compile your project dependencies (by running
kedro build-reqs behind the scenes) the first time you run
kedro install. If you don’t want Kedro to compile the requirements (for performance reasons, for example), run
kedro install --no-build-reqs. To recompile the requirements, run
kedro install --build-reqs. We recommend recompiling your requirements every time you update
Note: As project dependencies may evolve very quickly, we strongly recommend working with compiled requirements, which is the default behaviour of
kedro install, as mentioned above. This helps to keep your development environment reproducible, ensures compatibility between the dependencies and prevents version conflicts, which are often hard to debug.
pytest unit tests found in
src/tests, including coverage (see the file
Package your application as one
.egg file and one
.whl file within the
src/dist/ folder of your project. For further information about packaging for Python, documentation is provided here.
kedro jupyter notebook,
kedro jupyter lab,
Start a Jupyter Notebook, Lab or REPL session respectively.
Every time you start or restart a notebook kernel, a startup script (
<project-root>/.ipython/profile_default/startup/00-kedro-init.py) will add the following variables in scope:
ProjectContextclass defined in
src/project-name/run.py) (The details of how to use
contextcan be found here)
To reload these at any point in your notebook (e.g. if you updated
catalog.yml) use the line magic
This line magic can be also used to see the error message if any of the variables above are undefined.
Note: If you get an error message
Module ``<module_name>`` not found. Make sure to install required project dependencies by running ``kedro install`` command first.when running any of those commands, it indicates that some Jupyter or IPython dependencies are not installed in your environment. To resolve this you will need to a) make sure the corresponding dependency is present in
src/requirements.txtif not compiled), b) run
kedro installcommand from your terminal.
kedro jupyter convert¶
Copy the code from cells tagged with
node tag into Python files under
src/<package_name>/nodes/ in a Kedro project.
Typically output cells of Jupyter Notebook should not be tracked by git, especially if they contain sensitive information.
This command adds a
git hook which clears all notebook output cells before committing anything to
git. This needs to run only once per local repository.
kedro catalog list¶
This command shows datasets per pipeline per type. The result includes datasets that are/aren’t used by a specific pipeline. It also accept optional
--pipeline argument that allows specifying pipeline name(s) (comma-separated value) for which the datasets should be shown, e.g.
kedro catalog list --pipeline "ds,de".
kedro pipeline list¶
This command shows a list of all pipelines in your project.
kedro pipeline create¶
This command creates a new modular pipeline in your project. More details in this section.
kedro pipeline package <pipeline_name>¶
kedro pipeline delete <pipeline_name>¶
This command removes an existing modular pipeline from your project.
You can also invoke the Kedro CLI as a Python module:
python -m kedro