Machines and people collaborating together through Jupyter notebooks.
APACHE-2.0 License
This is a Python 3 library to read/write cells programmatically in
Jupyter notebooks <https://jupyter.org/>
_ which anticipates upcoming
collaborative <https://groups.google.com/forum/#!topic/jupyter/r7QSObF5YSg>
_
features in Jupyter.
We use this at O'Reilly Media <https://www.oreilly.com/>
_ for
notebooks used to manage machine learning pipelines.
That is to say, machines and people collaborate on documents,
implementing a "human-in-the-loop" design pattern:
jupyter notebook
via SSH tunnel for remote accessFor more info about use cases for this library and active learning
in general, see the JupyterCon 2017 <https://jupytercon.com/>
_ talk
Humans in the loop <https://conferences.oreilly.com/jupyter/jup-ny/public/schedule/detail/60058>
_
The following script generates a Jupyter notebook in the test.ipynb
file, then runs it:
::
python test.py
jupyter notebook
Then launch the test.ipynb
notebook and from the Cells
menu
select Run All
to view results.
NB: whenever you use the put_df()
function to store data as a
Pandas dataframe <https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html>
_
be sure to include import pandas as pd
at some earlier point in
the notebook.
This code has dependencies on:
nbformat <https://github.com/jupyter/nbformat>
_pandas <https://pandas.pydata.org/>
_To install from PyPi <https://pypi.python.org/pypi/nbtransom>
_:
::
pip install nbtransom
To install from this Git repo:
::
git clone https://github.com/ceteri/nbtransom.git
cd nbtransom
pip install -r requirements.txt
@htmartin <https://github.com/htmartin>
_
@esztiorm <https://github.com/esztiorm>
_
@fperez <https://github.com/fperez>
_
@odewahn <https://github.com/odewahn>
_