tutobooks 0.0.2

A simple package to convert between tutobooks python files, jupyter notebooks and

tutobooks

Note: All code credit to Francois Chollet, I simply bundled this into a pip package because I wanted to use it for more than keras.io

Taken from keras-io/scripts.

A tutobook is a tutorial available simultaneously as a notebook, as a Python script, and as a nicely rendered webpage.

Its source-of-truth (for manual edition and version control) is its Python script form, but you can also create one by starting from a notebook and converting it with the command nb2py.

Text cells are stored in markdown-formatted comment blocks. the first line (starting with " * 3) may optionally contain a special annotation, one of:

• invisible: do not render this block.
• shell: execute this block while prefixing each line with !.

The script form should start with a header with the following fields: Title: Author: (could be Authors: as well, and may contain markdown links) Date created: (date in yyyy/mm/dd format) Last modified: (date in yyyy/mm/dd format) Description: (one-line text description)

You would typically start from an existing notebook.

Save it to disk (let's say as path_to_your_nb.ipynb).

Then run:

python tutobooks nb2py path_to_your_nb.ipynb ../examples/your_example.py

This will create the file examples/your_example.py. Open it, fill in the headers, and generally edit it so that it looks nice.

NOTE THAT THE CONVERSION SCRIPT MAY MAKE MISTAKES IN ITS ATTEMPTS TO SHORTEN LINES. MAKE SURE TO PROOFREAD THE GENERATED .py IN FULL. Or alternatively, make sure to keep your lines reasonably-sized (<90 char) to start with, so that the script won't have to shorten them.

You can then preview what it looks like when converted back again to ipynb by running:

python tutobooks py2nb ../examples/your_example.py preview.ipynb

NOTE THAT THIS COMMAND WILL ERROR OUT IF ANY CELLS TAKES TOO LONG TO EXECUTE. In that case, make your code lighter/faster. Remember that examples are meant to demonstrate workflows, not train state-of-the-art models. They should stay very lightweight.

Open the generated preview.ipynb and make sure it looks like what you expect. If not, keep editing your_example.py until it does.

Finally, submit a PR adding examples/your_example.py. """