p2j 1.1.0

p2j: Convert Python scripts to Jupyter notebook with minimal intervention

p2j - Python to Jupyter Notebook

Convert your Python source code to Jupyter notebook with zero intervention.

The purpose of this package is to be able to run a code on Jupyter notebook without having to copy each paragraph of the code into every cell. It's also useful if we want to run our code in Google Colab.

In a nutshell, every paragraph of your code is transformed into a code cell.

This parser isn't perfect, but you would be satisfactorily pleased with what you get.

See an example of a Python source code and its Jupyter notebook after converting.

Installing

pip install p2j

Running

p2j code_to_parse.py

and you will get a code_to_parse.ipynb Jupyter notebook. See p2j -h for other arguments.

To run examples from this repository, first clone this repo

git clone https://github.com/raibosome/python2jupyter.git

and after you cd into the project, run

p2j examples/example.py

The examples/example.py is a Keras tutorial on building an autoencoder for the MNIST dataset, found here.

Tests

Tested on macOS 10.14 with Python 3.6.

How it works

Jupyter notebooks are just JSON files. The py2nb.py reads the source code line-by-line and determines whether it should be a markdown cell or a code cell, using a rule-based method. It also respects the following:

• Blocks of indented code. Comments from within are kept as a code cell. Eg. classes, function definitions and loops
• Docstrings
• Pylint directives are converted to code cells

Project Structure

├── p2j             The parser module
│   ├── __init__.py
│   ├── examples    Example codes that you can parse
│   ├── p2j.py      Main file
│   └── templates   JSON files needed to build the notebook
├── README.md       This file
├── LICENSE         Licensing
├── MANIFEST.in     Python packaging-related
├── build           Python packaging-related
├── dist            Python packaging-related
├── p2j.egg-info    Python packaging-related
└── setup.py        Python packaging-related

Code format

There is no specific format that you should follow, but generally the parser assumes a format where your code is paragraphed. Each paragraph has the comments part and/or the code part. The comments will be automatically converted to a markdown cell while the code will be, you guessed it, the code cell.

Some examples of well-documented code (and from which you can test!):

• PyTorch Tutorials
• Keras Examples
• Scikit Learn Example

Pull requests

Pull requests are very much encouraged!