How to Dockerize

Create a file named Dockerfile

Add the base Image

# In Dockerfile
FROM ubuntu

Build and Tag the Image

docker build -t <YOUR DOCKER HUB USERNAME>/<YOUR IMAGE NAME> .

Create the Container

docker run -it <YOUR DOCKER HUB USERNAME>/<YOUR IMAGE NAME>

Verify that the Container is a different OS

cat /etc/lsb-release

You should see output similar to:

root@854c4e712040:/project# cat /etc/lsb-release
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=20.04
DISTRIB_CODENAME=focal
DISTRIB_DESCRIPTION="Ubuntu 20.04.3 LTS"

Update Dockerfile

FROM ubuntu

# Update default OS packages
RUN apt-get update && apt-get install -y software-properties-common gcc vim && \
    add-apt-repository -y ppa:deadsnakes/ppa

# Install python
RUN apt-get update && apt-get install -y python3.8 python3-distutils python3-pip python3-apt

# Copy requirements.txt from the project into the Docker Image
COPY requirements.txt requirements.txt

# Install project dependencies
RUN pip3 install -r requirements.txt

# Make folder called /project and cd into it
WORKDIR /project

COPY . .

Recreate the Container

docker run -it <YOUR DOCKER HUB USERNAME>/<YOUR IMAGE NAME>

Run the script

With the project in our new container we can now run

python3 cleaner.py

and we should see output like

root@8e4f4b252200:/project# python3 cleaner.py 
    Duration       Date  Pulse  Maxpulse  Calories
0         60 2020-12-01    110       130    409.10
1         60 2020-12-02    117       145    479.00
2         60 2020-12-03    103       135    340.00
3         45 2020-12-04    109       175    282.40
4         45 2020-12-05    117       148    406.00
...

and if you run ls the plot.png should be generated.

root@8e4f4b252200:/project# ls
Dockerfile  README.md  cleaner.py  data.csv  plot.png  requirements.txt

Push to Docker Hub

docker push <YOUR DOCKER HUB USERNAME>/<YOUR IMAGE NAME>