# Lesson 0 - Getting started¶

## Overview¶

In this lesson, we will cover the basics of getting started with the WRF-Hydro training environment.

### Requirements¶

The easiest and recommended way to run these lessons is via the wrfhydro/costarica-training Docker container, which has all software dependencies and data pre-installed.

- Docker >= v.17.12
- Web browser (Google Chrome recommended)

### Where to get help and/or post issues¶

If you have general questions about Docker, there are ample online resources including the excellent Docker documentation at https://docs.docker.com/.

The best place to ask questions or post issues with these lessons is via the Issues page of the GitHub repository at https://github.com/NCAR/wrf_hydro_training/issues.

## How to run¶

Make sure you have Docker installed and that it can access your localhost ports. Most out-of-the-box Docker installations accepting all defaults will have this configuration.

Step 1: Open a terminal or PowerShell session

Step 2: Pull the wrfhydro/costarica-training Docker container

Note: For in person WRF-Hydro trainings this has been done for you. DO NOT pull the container.

Issue the following command in your terminal to pull the training container.

`docker pull wrfhydro/costarica-training`

Step 3: Start the training container

Issue the following command in your terminal session to start the Docker container.

`docker run --name wrf-hydro-training -p 8888:8888 -it wrfhydro/costarica-training`

The container will start and perform a number of actions before starting the training.

Note: If you have already started the training once you will need to remove the previous container using the following command: `docker rm wrf-hydro-training`

Step 4: Connect to Jupyter Notebook server using your browser

At the end of the container startup process an address and password will be printed to the terminal. The address and password are used to connect to the container Jupyter Notebook server. All training lesson notebooks in this container are in the `/home/docker/wrf-hydro-training/lessons` directory and can be opened in your browser using Jupyter.

## What is included¶

- The model code
- An example test case
- WRF-Hydro training lessons as Jupyter notebooks
- Jupyter notebook server

Note: Port forwarding is setup with the `-p 8888:8888` argument, which maps your localhost port to the container port. If you already have something running on port 8888 on your localhost you will need to change this number