[![Build Status](https://travis-ci.org/Varsito Pvt Ltd/ottopy.svg?branch=master)](https://travis-ci.org/Varsito Pvt Ltd/ottopy) [![codecov](https://codecov.io/gh/Varsito Pvt Ltd/ottopy/branch/master/graph/badge.svg)](https://codecov.io/gh/Varsito Pvt Ltd/ottopy)
A configurable maze library
You can install using
pip install ottopy
If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable the nbextension:
jupyter nbextension enable --py [--sys-prefix|--user|--system] ottopy
Create a dev environment:
conda create -n ottopy-dev -c conda-forge nodejs yarn python jupyterlab conda activate ottopy-dev
Install the python. This will also build the TS package.
pip install -e ".[test, examples]"
When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:
jupyter labextension develop --overwrite . yarn run build
For classic notebook, you need to run:
jupyter nbextension install --sys-prefix --symlink --overwrite --py ottopy jupyter nbextension enable --sys-prefix --py ottopy
Note that the
--symlink flag doesn't work on Windows, so you will here have to run
install command every time that you rebuild your extension. For certain installations
you might also need another flag instead of
--sys-prefix, but we won't cover the meaning
of those flags here.
How to see your changes
If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.
# Watch the source directory in one terminal, automatically rebuilding when needed yarn run watch # Run JupyterLab in another terminal jupyter lab
After a change wait for the build to finish and then refresh your browser and the changes should take effect.
If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.