# Minimal C kernel for Jupyter

## Use with Docker (recommended)

 * `docker pull brendanrius/jupyter-c-kernel`
 * `docker run -p 8888:8888 brendanrius/jupyter-c-kernel`
 * Copy the given URL containing the token, and browse to it.

## Manual installation

 * Make sure you have the following requirements installed:
  * gcc
  * jupyter
  * python 3
  * pip

### Step-by-step:
 * `pip install jupyter-c-kernel`
 * `install_c_kernel`
 * `jupyter-notebook`. Enjoy!

## Example of notebook

![Example of notebook](example-notebook.png?raw=true "Example of notebook")

## Custom compilation flags

You can use custom compilation flags like so:

![Custom compulation flag](custom_flags.png?raw=true "Example of notebook using custom compilation flags")

Here, the `-lm` flag is passed so you can use the math library.

## Contributing

The docker image installs the kernel in editable mode, meaning that you can
change the code in real-time in Docker. For that, just run the docker box like
that:

```bash
git clone https://github.com/brendan-rius/jupyter-c-kernel.git
cd jupyter-c-kernel
docker run -v $(pwd):/jupyter/jupyter_c_kernel/ -p 8888:8888 brendanrius/jupyter-c-kernel
```

This clones the source, run the kernel, and binds the current folder (the one
you just cloned) to eh corresponding folder in Docker.
Now, if you change the source, it will be reflected in [http://localhost:8888](http://localhost:8888)
instantly. Do not forget to click "restart" the kernel on the page as it does
not auto-restart.

### Version control

Create branches named `issue-X` where `X` is the number of the issue.
Rebase instead of merge.

## License

[MIT](LICENSE.txt)