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Tools to work with Jupyter notebooks

Project Description

  • validate: validate notebooks
  • head: show head or tail of notebooks
  • dump: dump notebook info and source on terminal
  • stats: summarize notebooks with statistics
  • view: view notebook, including all embedded images, LaTeX, and HTML in a browser
  • cat: catenate multiple notebooks
  • clean: clean notebooks by removing specified elements
  • run: execute notebooks, with pre/post cleaning
  • split: split notebooks into MarkDown, code, and raw
  • punch: punch holes into notebooks and fill them (for creating exercises)

Available as library functions and as configurable command-line scripts.

Installation

pip install nbtoolbelt

Documentation

Documentation is available on Read the Docs.

On the command line, you can use the options -h or --help.

Usage

On the command line:

nbtb [-h] [options] tool [options] nb.ipynb ...

As library: see documentation

Testing

pip install nbtoolbelt[test]

nbtoolbelt comes with a set of automatic test cases for pytest.

Developing

Some useful commands, and where to run them:

  • In nbtoolbelt/docs/,
    • clean build directory: make clean
    • create html documentation tree: make html
    • create pdf documentation: make latexpdf
    • determine size of documentation: wc `find . -name '*.rst'`
  • In nbtoolbelt/test/,
    • run all test cases: pytest .
  • In nbtoolbelt/,
    • test package configuration: python setup.py check -r -s
    • create source distribution and wheel: python setup.py sdist bdist_wheel
  • In nbtoolbelt/dist/
    • create digital signature: gpg --detach-sign -a ...
    • upload to PyPI: twine upload ...
  • In nbtoolbelt/src/,
    • determine size of code: wc `find . -name '*.py'`

License

Copyright (c) 2017 - Eindhoven University of Technology, The Netherlands

This software is made available under the terms of the MIT License.

Resources

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2018.2.dev0

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2018.1.dev0

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2017.11.dev1

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2017.10.dev5

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2017.10.dev3

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2017.10.dev2

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