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Next generation slides from Jupyter Notebooks

Project description

# nbpresent > remix your Jupyter Notebooks as interactive slideshows

## Installation `shell pip install nbpresent python -m nbpresent.install `

Then either run `python %reload_ext nbpresent `

_every time you start the notebook or _enable_ the extension for every notebook launch: `shell python -m nbpresent.install --enable `

### Coming soon - [conda package](https://github.com/ContinuumIO/nbpresent/issues/1)

## Export Stock nbconvert doesn’t store quite enough information, so you’ll need to do something like this: `shell python -m nbpresent.present notebooks/README.ipynb > README.html ` The resulting file can be hosted and viewed (but not edited!) on any site with fallback to Github.

## Development There are several development scenarios

### The Hard Way The nbpresent nbextension is built from src in a checked out repo with: - less for style - babel for es2015 - browserify for packaging

These are installed via npm: `shell npm install `

To build everything with sourcemaps: `shell npm run build `

To rebuild on every save: `shell npm run watch `

To build everything, and optimize it: `shell npm run build `

To ensure that you always get the right assets, install the nbextension with the symlink, force and enable options: `shell python -m nbpresent.install --overwrite --symlink --enable --user `

### Developing with conda A conda package, which pre-builds the static assets and installs itself into the local conda environment, is built from conda.recipe

` conda build conda.recipe `

When developing with conda, you may want to use your conda environment to store assets and configuration: `shell python -m nbpresent.install --overwrite --symlink --enable --prefix="${CONDA_ENV_PATH}" `

### Developing with docker compose A number of intermediate Dockerfiles are available for different development workflows. These are most easily managed with docker-compose.

For building a pristine conda environment, use conda_base. For a build of nbpresent, with all tests, use conda_build. For a live, running notebook with nbpresent installed, use conda.

>> META: TODO: make templates?

Here is the build chain:

`shell docker-compose build conda_base && \ docker-compose build conda_build && \ docker-compose build conda && \ docker-compose up conda `

> META: force build 1

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