https://github.com/pgmccann/nbbdd

BDD for Jupyter Notebooks. Hackday project at SSI Collaborations Workshop 2020. #CollabW2020
https://github.com/pgmccann/nbbdd

bdd behavior-driven-development collabw20 gherkin jupyter jupyter-notebook jupyter-notebooks python

Last synced: about 2 months ago
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BDD for Jupyter Notebooks. Hackday project at SSI Collaborations Workshop 2020. #CollabW2020

• Host: GitHub
• URL: https://github.com/pgmccann/nbbdd
• Owner: pgmccann
• License: mit
• Created: 2020-04-02T07:53:21.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-04-02T15:02:13.000Z (over 4 years ago)
• Last Synced: 2023-10-19T18:17:07.932Z (about 1 year ago)
• Topics: bdd, behavior-driven-development, collabw20, gherkin, jupyter, jupyter-notebook, jupyter-notebooks, python
• Language: Python
• Homepage:
• Size: 37.1 KB
• Stars: 2
• Watchers: 3
• Forks: 3
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.cff

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README

        
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

# BDD for Jupyter Notebooks

This is a Hackday project at the [SSI Collaborations Workshop

2020](https://www.software.ac.uk/cw20).

This is a Python-based command-line tool for parsing

[Gherkin code](https://cucumber.io/docs/gherkin/reference/) in Markdown cells

in a [Jupyter](https://jupyter.org/) Notebook and generating skeleton unit

tests which are then inserted into the Notebook at the appropriate points.

The idea of this project is improve the Jupyter notebooks by adding validations but all

this is not something new, there is already something available as a plug in for Jupyter called [nbval](https://github.com/computationalmodelling/nbval)

which work nice if you want to use the TDD approach which sometime can be a little bit painful when you are in an 

early stage prototyping you research. Since TDD (Test Driven Development) can be a little be to much from the beginning we found that it may be helpful

to start with a BDD (Behavior-driven development) approach by writing test cases in a natural language that 

non-programmers can read and also serve as a documentation more or less.

# The basic workflow will be:

1. Create initial notebook

2. Start writing test cases using natural language combined with Gherkin behaviour markup

3. [nbbdd](https://github.com/pgmccann/nbbdd) generates feature and skeleton step files, inserts step code, returns failing test results

4. Populate skeleton tests with real test code

5. Start write software while keeping in mind running also the tests until all pass

Some simple example for step 2 using [behave ](http://behave.github.io/behave.example/tutorials/tutorial02.html)

    

    Feature: Fight or Flight (Natural Language, tutorial02)

    

        In order to increase the ninja survival rate,

        As a ninja commander

        I want my ninjas to decide whether to take on an opponent

        based on their skill levels.

        Scenario: Weaker opponent

            Given the ninja has a third level black-belt

            When attacked by a samurai

            Then the ninja should engage the opponent

    

        Scenario: Stronger opponent

            Given the ninja has a third level black-belt

            When attacked by Chuck Norris

            Then the ninja should run for his life

Steps 4 and 5 can be identified as the TDD part which already requires some coding skills. 

# Acknowledgements

This [paper](https://www.researchgate.net/publication/338594130_Testing_with_Jupyter_notebooks_NoteBook_VALidation_nbval_plug-in_for_pytest) helped a lot to understand what should be achieved during the hackday:

Fangohr, H. & Fauske, Vidar & Kluyver, Thomas & Albert, Maximilian & Laslett, Oliver & Cortés-Ortuño, David & Beg, Marijan & Ragan-Kelly, Min. (2020). Testing with Jupyter notebooks: NoteBook VALidation (nbval) plug-in for pytest.