This is a Python 3 library to read/write cells programmatically in Jupyter notebooks which anticipates upcoming collaborative features in Jupyter.
We use this at O’Reilly Media 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:
people adjust hyperparameters for the ML pipelines
machines write structured “logs” during ML modeling/evaluation
people run jupyter notebook via SSH tunnel for remote access
For more info about use cases for this library and active learning in general, see the JupyterCon 2017 talk Humans in the loop
Example Usage
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 be sure to include import pandas as pd at some earlier point in the notebook.
Dependencies and Installation
This code has dependencies on:
To install from PyPi:
pip install nbtransom
To install from this Git repo:
git clone https://github.com/ceteri/nbtransom.git cd nbtransom pip install -r requirements.txt
Kudos
1 maintainer
Metadata
1 maintainer
Release files for nbtransom 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| nbtransom-1.0.1.tar.gz | 4.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nbtransom-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.4 kB
Release files / nbtransom-1.0.1.tar.gz
| Download URL | nbtransom-1.0.1.tar.gz |
|---|---|
| Size | 4.2 kB |
| Tags | Source |
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Release files / nbtransom-1.0.1-py3-none-any.whl
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|---|---|
| Size | 6.2 kB |
| Tags | Python 3 |
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