## Getting started

This document describes some of the basics of installing and running the Jupyter Kernel Gateway.

### Using pip

We make stable releases of the kernel gateway to PyPI. You can use pip to install the latest version along with its dependencies.

`bash # install from pypi pip install jupyter_kernel_gateway `

Once installed, you can use the jupyter CLI to run the server.

`bash # run it with default options jupyter kernelgateway `

### Using conda

You can install the kernel gateway using conda as well.

`bash conda install -c conda-forge jupyter_kernel_gateway `

Once installed, you can use the jupyter CLI to run the server as shown above.

### Using a docker-stacks image

You can add the kernel gateway to any [docker-stacks](https://github.com/jupyter/docker-stacks) image by writing a Dockerfile patterned after the following example:

```bash # start from the jupyter image with R, Python, and Scala (Apache Toree) kernels pre-installed FROM jupyter/all-spark-notebook

# install the kernel gateway RUN pip install jupyter_kernel_gateway

# run kernel gateway on container start, not notebook server EXPOSE 8888 CMD [“jupyter”, “kernelgateway”, “–KernelGatewayApp.ip=0.0.0.0”, “–KernelGatewayApp.port=8888”] ```

You can then build and run it.

`bash docker build -t my/kernel-gateway . docker run -it --rm -p 8888:8888 my/kernel-gateway `