Using containers with Docker

.title[
# Using containers with Docker<br />
<html><br />
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<hr color='#EB811B' size=1px width=796px><br />
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.author[
### Rockefeller University, Bioinformatics Resource Centre
]
.date[
### <a href="https://rockefelleruniversity.github.io/RU_reproducibleR/" class="uri">https://rockefelleruniversity.github.io/RU_reproducibleR/</a>
]

---

## Set Up

All prerequisites, links to material and slides for this course can be found on github.

* [Reproducible_R](https://rockefelleruniversity.github.io/RU_reproducibleR/)

Or can be downloaded as a zip archive from here.

* [Download zip](https://github.com/RockefellerUniversity/RU_reproducibleR/archive/master.zip)

---
## Course materials

Once the zip file in unarchived. All presentations as HTML slides and pages, their R code and HTML practical sheets will be available in the directories underneath.

* **presentations/slides/**
Presentations as an HTML slide show.
* **presentations/singlepage/** 
Presentations as an HTML single page.
* **presentations/r_code/**
R code in presentations.
* **exercises/**
Practicals as HTML pages. 
* **answers/**
Practicals with answers as HTML pages and R code solutions. 
* **data/**
Data used in this presentation.

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class: inverse, center, middle

# What are containers? <br> Why should we use them?

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## The problem
Something works on your computer (e.g. bioinformatics analysis or software deployment), and you want to make sure that it will work on another computer.

<font size='1'><a href="https://jhudatascience.org/Adv_Reproducibility_in_Cancer_Informatics/launching-a-docker-image.html">https://jhudatascience.org/Adv_Reproducibility_in_Cancer_Informatics/launching-a-docker-image.html - </a><a href="https://creativecommons.org/licenses/by/4.0">CC-BY 4.0</a></font>

---

## The solution - Docker!

Docker allows for the creation of an isolated environment that can be shipped across different users, machines, or operating systems, and to virtual machines or the cloud.

---

## Docker client and host

Once installed on your computer, Docker runs a process called the Docker daemon. A daemon is a program that runs as a background process and is not under direct control of the computer user, and the Docker daemon is the engine that manages Docker services and objects by communicating with the client.

The Docker client, typically the command line interface, communicates with the Docker daemon based on [user commands.](https://docs.docker.com/engine/reference/commandline/cli/)

---

## Creating Docker images

The 'docker image build' command uses a Dockerfile to create an image.

A Docker image is a read-only, isolated file system that contains all software, dependencies, scripts, and metadata required to run a container.

---

## Launching Docker containers

Once an image is built, an instance of this image can be launched as a stand-alone application, also known as a container.

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## Pulling Docker images

There are public repositories of Docker images (e.g. [Docker Hub](https://hub.docker.com/)), and typically you start with an existing image and build on top of this.

---

## Installing Docker

Use [this link](https://www.docker.com/get-started/) to install Docker.

* Click on the Docker desktop icon and make an account with Docker.
* Docker must be open and running to use the command line interface (CLI), which is how we will primarily use Docker.
* [See here](https://docs.docker.com/engine/reference/commandline/cli/) for Docker CLI commands.

Check Docker version to make sure Docker is installed and running.

*Code (terminal):*

``` sh
docker --version
```

*Output:*

---

## Installing Docker

If previous command isn't found check the Docker Desktop advanced settings and make sure CLI tools are available system-wide.

---

# Running Docker containers<br>from Docker Hub images

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## Pulling Docker images - Rocker

[Rocker](https://rocker-project.org/) is a very useful source of images on Docker Hub for R and RStudio. We can pull these images immediately after installing Docker. Here we pull an image containing RStudio and a specific version of R.

*Code (terminal):*

``` sh
docker image pull rocker/rstudio:4.4.0
# alias of 'docker pull' from older Docker versions
```

---

## Viewing local Docker images

After pulling, the image is now available on our system to run.

Images have names, tags, and image IDs as shown in the output. The ID is a hash of the metadata and filesystem of the Docker image.

*Code (terminal):*

``` sh
docker images
```

*Output:*

---

## Viewing local Docker images

After pulling, the image is now available on our system to run.

Images have names, tags, and image IDs as shown in the output. The ID is a hash of the metadata and filesystem of the Docker image.

We can also view the image in Docker desktop:
<img src="imgs/docker_desktop_images.png" width="80%" style="display: block; margin: auto;" />

---

## Running Docker containers

Once the image is on our system, we can launch a container with the ['docker container run' command](https://docs.docker.com/engine/reference/commandline/run/).

Components of the run command:
*  --rm: this will automatically remove a container when you exit, otherwise can take up room on computer with old, unused containers
*  -p: before the colon is the port on your computer to be exposed and after the colon is the port inside the container
*  -e: an environmental variable is set when the container is run, and this will be the password to login
*  the last argument is the image name and tag (both seen with 'docker images')

*Code (terminal):*

``` sh
docker container run --rm \
               -p 8787:8787 \
               -e PASSWORD=password123 \
               rocker/rstudio:4.4.0
# alias of 'docker run' from older Docker versions
```

---

## Running Docker containers

While the container is running, we can go to 'http://localhost:8787' in a browser and log in with the the user 'rstudio' and the password from 'docker container run'.

---

## Listing active Docker containers

To see all containers running in the local environment, use the 'docker container ls' command

*Code (terminal):*

``` sh
docker container ls
# alias of 'docker ps' from older Docker versions
```

*Output:*

---

## Stopping Docker containers

To stop the container currently running, if you are in the terminal tab where it was launched press Ctrl+C.

Or open up another tab and the 'docker stop' command can be used with the ID listed from 'docker container ls'

*Code (terminal):*

``` sh
docker container stop 8b1619f9189d # this is the ID from 'docker container ls'
docker container ls
```

*Output:*

---