$ kedro jupyter notebook

$ kedro jupyter lab

$ kedro ipython

In [1]:
In [2]: exit()

$ kedro new --starter=pandas-iris
$ cd iris
$ kedro jupyter notebook

In [1]: catalog.list()

[
    'example_iris_data',
    'parameters',
    'params:train_fraction',
    'params:random_state',
    'params:target_column'
]

In [2]: catalog.load("example_iris_data")

INFO     Loading data from 'example_iris_data' (CSVDataSet)...
	sepal_length	sepal_width	petal_length	petal_width	species
0	  5.1	          3.5	        1.4	          0.2	        setosa
1	  4.9	          3.0	        1.4	          0.2	        setosa
2	  4.7	          3.2	        1.3	          0.2	        setosa
3	  4.6	          3.1	        1.5	          0.2	        setosa
4	  5.0	          3.6	        1.4	          0.2	        setosa
...	...	          ...	        ...	          ...	        ...
145	6.7	          3.0	        5.2	          2.3	        virginica
146	6.3	          2.5	        5.0	          1.9	        virginica
147	6.5	          3.0	        5.2	          2.0	        virginica
148	6.2	          3.4	        5.4	          2.3	        virginica
149	5.9	          3.0	        5.1	          1.8	        virginica

150 rows × 5 columns

In [3]: catalog.load("parameters")

INFO     Loading data from 'parameters' (MemoryDataSet)...
{'train_fraction': 0.8, 'random_state': 3, 'target_column': 'species'}

In [4]: context.project_path

PosixPath('/Users/ryu/iris')

In [5]: pipelines

{'__default__': Pipeline([
Node(split_data, ['example_iris_data', 'parameters'], ['X_train', 'X_test', 'y_train', 'y_test'], 'split'),
Node(make_predictions, ['X_train', 'X_test', 'y_train'], 'y_pred', 'make_predictions'),
Node(report_accuracy, ['y_pred', 'y_test'], None, 'report_accuracy')
])}

In [6]: pipelines["__default__"].all_outputs()

{'y_test', 'y_train', 'X_test', 'y_pred', 'X_train'}

In [7]: session.run()

[01/15/23 09:24:05] INFO     Kedro project iris                                                      session.py:340
[01/15/23 09:24:06] INFO     Loading data from 'example_iris_data' (CSVDataSet)...              data_catalog.py:343
                    INFO     Loading data from 'parameters' (MemoryDataSet)...                  data_catalog.py:343
                    INFO     Running node: split: split_data([example_iris_data,parameters]) ->         node.py:327
                             [X_train,X_test,y_train,y_test]
                    INFO     Saving data to 'X_train' (MemoryDataSet)...                        data_catalog.py:382
                    INFO     Saving data to 'X_test' (MemoryDataSet)...                         data_catalog.py:382
                    INFO     Saving data to 'y_train' (MemoryDataSet)...                        data_catalog.py:382
                    INFO     Saving data to 'y_test' (MemoryDataSet)...                         data_catalog.py:382
                    INFO     Completed 1 out of 3 tasks                                     sequential_runner.py:85
                    INFO     Loading data from 'X_train' (MemoryDataSet)...                     data_catalog.py:343
                    INFO     Loading data from 'X_test' (MemoryDataSet)...                      data_catalog.py:343
                    INFO     Loading data from 'y_train' (MemoryDataSet)...                     data_catalog.py:343
                    INFO     Running node: make_predictions: make_predictions([X_train,X_test,y_train]) node.py:327
                             -> [y_pred]
                    INFO     Saving data to 'y_pred' (MemoryDataSet)...                         data_catalog.py:382
                    INFO     Completed 2 out of 3 tasks                                     sequential_runner.py:85
                    INFO     Loading data from 'y_pred' (MemoryDataSet)...                      data_catalog.py:343
                    INFO     Loading data from 'y_test' (MemoryDataSet)...                      data_catalog.py:343
                    INFO     Running node: report_accuracy: report_accuracy([y_pred,y_test]) -> None    node.py:327
                    INFO     Model has accuracy of 0.933 on test data.                                  nodes.py:74
                    INFO     Completed 3 out of 3 tasks                                     sequential_runner.py:85
                    INFO     Pipeline execution completed successfully.                                runner.py:90

In [8]: %reload_kedro

[01/15/23 09:25:42] INFO     Resolved project path as: /Users/ryu/iris.         __init__.py:132
                             To set a different path, run '%reload_kedro <project_root>'
[01/15/23 09:25:43] INFO     Kedro project Iris                                                     __init__.py:101
                    INFO     Defined global variable 'context', 'session', 'catalog' and            __init__.py:102
                             'pipelines'
                    INFO     Registered line magic 'run_viz'                                        __init__.py:108

In [9]: %reload_kedro?

Docstring:
::

  %reload_kedro [-e ENV] [--params PARAMS] [path]

The `%reload_kedro` IPython line magic. See
 https://kedro.readthedocs.io/en/stable/tools_integration/ipython.html for more.

positional arguments:
  path               Path to the project root directory. If not given, use the
                     previously setproject root.

optional arguments:
  -e ENV, --env ENV  Kedro configuration environment name. Defaults to
                     `local`.
  --params PARAMS    Specify extra parameters that you want to pass to the
                     context initializer. Items must be separated by comma,
                     keys - by colon, example: param1:value1,param2:value2.
                     Each parameter is split by the first comma, so parameter
                     values are allowed to contain colons, parameter keys are
                     not. To pass a nested dictionary as parameter, separate
                     keys by '.', example: param_group.param1:value1.
File:      ~/Program/MLOps/kedro/venv/lib/python3.8/site-packages/kedro/ipython/__init__.py

In [10]: %run_viz

def some_action():
    print("This function came from `notebooks/my_notebook.ipynb`")

$ mv my_notebook.ipynb notebooks

$ kedro jupyter convert notebooks/my_notebook.ipynb

$ cat src/iris/nodes/my_notebook.py

def some_action():
    print("This function came from `notebooks/my_notebook.ipynb`")