https://github.com/chrisgschon/docker-for-ds

A practical introduction to Docker for data science
https://github.com/chrisgschon/docker-for-ds

Last synced: 2 months ago
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A practical introduction to Docker for data science

• Host: GitHub
• URL: https://github.com/chrisgschon/docker-for-ds
• Owner: chrisgschon
• License: mit
• Created: 2019-05-07T10:03:58.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-05-13T15:58:30.000Z (about 5 years ago)
• Last Synced: 2024-01-24T00:47:33.624Z (5 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 8.79 KB
• Stars: 10
• Watchers: 2
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• my-awesome-stars - chrisgschon/docker-for-ds - A practical introduction to Docker for data science (Jupyter Notebook)

README

        
# 👨🏼‍💻 docker-for-ds

A practical introduction to Docker for data scientists, showing how to use and combine Jupyter and MSSQL Server in local isolated Docker containers.

The medium post [here](https://medium.com/applied-data-science/the-full-stack-data-scientist-part-2-a-practical-introduction-to-docker-1ea932c89b57) for the longer tutorial. 

## 🐳 Starting with Docker

- Install Docker. This is a straightforward download from the [docs](https://docs.docker.com/install/).

- Open up the app and make sure there's a green light telling you it's running.

- Follow the [hello-world tutorial](https://docs.docker.com/samples/library/hello-world/) to double check the installation works properly.

## 🆙 Walkthrough

We will be running two separate Docker containers:

1. An ubuntu xenial container to run python code in Jupyter notebooks

2. An MSSSQL Server linux container to host our  database

Open a terminal in the root of the repo and run the following commands:

```docker-compose build```

*Builds the images with docker-compose.yml acting as the configuration*

```docker-compose up -d```

*Spins up the containers*

```docker-compose exec app bash```

*Runs bash from inside the 'app' container*

You will be inside the container's terminal now, run:

```jupyter notebook --ip 0.0.0.0 --no-browser --allow-root```

Using the provided token, enter this into your browser

```http://localhost:8888/?token=URTOKEN```

✅ The token provides a security measure to make sure hackers can't access your code and data!

🎮 Running the notebook will extract Ninja's current Fortnite stats and load them into a fortnite table in your MSSQL instance. View your output table in a database management app. I like to use DBeaver.

## How to only build the Jupyter environment

Open a terminal and navigate to /app, then run

```docker build -t ds . ```

*builds image with tag 'ds'*

```docker run --rm -it -p 8888:8888 ds```

*runs the ds image with notebook ports mapped*