pip install soorgeon

# works with ipynb files
soorgeon test path/to/notebook.ipynb
# and notebooks in percent format
soorgeon test path/to/notebook.py

soorgeon test path/to/notebook.ipynb path/to/output.ipynb
soorgeon test path/to/notebook.py path/to/output.ipynb

# refactor notebook
soorgeon refactor nb.ipynb
# all variables with the df prefix are stored in csv files
soorgeon refactor nb.ipynb --df-format csv
# all variables with the df prefix are stored in parquet files
soorgeon refactor nb.ipynb --df-format parquet
# store task output in 'some-directory' (if missing, this defaults to 'output')
soorgeon refactor nb.ipynb --product-prefix some-directory
# generate tasks in .py format
soorgeon refactor nb.ipynb --file-format py
# use alternative serializer (cloudpickle or dill) if notebook 
# contains variables that cannot be serialized using pickle 
soorgeon refactor nb.ipynb --serializer cloudpickle
soorgeon refactor nb.ipynb --serializer dill

git clone https://github.com/ploomber/soorgeon

cd soorgeon/examples/exploratory
soorgeon refactor nb.ipynb
# to run the pipeline
pip install -r requirements.txt
ploomber build

cd soorgeon/examples/machine-learning
soorgeon refactor nb.ipynb
# to run the pipeline
pip install -r requirements.txt
ploomber build